1 2 3<!doctype html> 4<!-- 5 Minimal Mistakes Jekyll Theme 4.28.1 by Michael Rose 6 Copyright 2013-2026 Michael Rose - mademistakes.com | @mmistakes 7 Copyright 2024-2026 iBug - ibugone.com | @iBug 8 Free for personal and commercial use under the MIT license 9 https://github.com/mmistakes/minimal-mistakes/blob/master/LICENSE 10--> 11 12<html lang="en" class="no-js" dir="ltr"> 13 <head> 14 15<meta charset="utf-8"> 16 17 18<!-- begin _includes/seo.html --><title>Papers - CAVA Lab</title> 19<meta name="description" content="Clinical AI Value Alignment"> 20 21 22 23<meta property="og:type" content="website"> 24<meta property="og:locale" content="en_US"> 25<meta property="og:site_name" content="CAVA Lab"> 26<meta property="og:title" content="Papers"> 27<meta property="og:url" content="https://cavalab.github.io/papers/"> 28 29 30 <meta property="og:description" content="Clinical AI Value Alignment"> 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45<link rel="canonical" href="https://cavalab.github.io/papers/"> 46 47 48 49 50 51 52 53 54 55 56 57 58<!-- end _includes/seo.html --> 59 60 61<meta name="viewport" content="width=device-width, initial-scale=1.0"> 62
63<script> 64 document.documentElement.className = document.documentElement.className.replace(/\bno-js\b/g, '') + ' js '; 65 66</script>
66 67 68<!-- For all browsers --> 69<link rel="stylesheet" href="/assets/css/main.css"> 70<link rel="preload" href="https://cdn.jsdelivr.net/npm/@fortawesome/fontawesome-free@latest/css/all.min.css" as="style" onload="this.onload=null;this.rel='stylesheet'"> 71<noscript><link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/@fortawesome/fontawesome-free@latest/css/all.min.css"></noscript> 72 73 74 75 <!-- Load KaTeX for math rendering --> 76<!-- https://varunagrawal.github.io/2018/03/27/latex-jekyll/ --> 77<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/[email protected]/dist/katex.min.css" integrity="sha384-Xi8rHCmBmhbuyyhbI88391ZKP2dmfnOl4rT9ZfRI7mLTdk1wblIUnrIq35nqwEvC" crossorigin="anonymous"> 78 79<!-- The loading of KaTeX is deferred to speed up page rendering -->
80<script defer src="https://cdn.jsdelivr.net/npm/[email protected]/dist/katex.min.js" integrity="sha384-X/XCfMm41VSsqRNQgDerQczD69XqmjOOOwYQvr/uuC+j4OPoNhVgjdGFwhvN02Ja" crossorigin="anonymous"></script>
80 81 82<!-- To automatically render math in text elements, include the auto-render extension: -->
83<script defer src="https://cdn.jsdelivr.net/npm/[email protected]/dist/contrib/auto-render.min.js" integrity="sha384-+XBljXPPiv+OzfbB3cVmLHf4hdUFHlWNZN5spNQ7rmHTXpd7WvJum6fIACpNNfIR" crossorigin="anonymous" 84 onload="renderMathInElement(document.body);"></script>
84 85 86<!-- insert favicons. use https://realfavicongenerator.net/ --> 87 88<link rel="apple-touch-icon" sizes="180x180" href="/assets/images/apple-touch-icon.png"> 89<link rel="icon" type="image/png" sizes="32x32" href="/assets/images/favicon-32x32.png"> 90<link rel="icon" type="image/png" sizes="16x16" href="/assets/images/favicon-16x16.png"> 91<link rel="manifest" href="/assets/images/site.webmanifest"> 92<link rel="shortcut icon" href="/assets/images/favicon.ico"> 93<meta name="msapplication-TileColor" content="#da532c"> 94<meta name="msapplication-config" content="/assets/images/browserconfig.xml"> 95<meta name="theme-color" content="#ffffff"> 96 97 </head> 98 99 <body class="layout--archive wide"> 100 101<nav class="skip-links" aria-label="Skip links"> 102 <ul> 103 <li><a href="#site-nav" class="screen-reader-shortcut">Skip to primary navigation</a></li> 104 <li><a href="#main" class="screen-reader-shortcut">Skip to content</a></li> 105 <li><a href="#footer" class="screen-reader-shortcut">Skip to footer</a></li> 106 </ul> 107</nav> 108 109 110 111 112<div class="masthead"> 113 <div class="masthead__inner-wrap"> 114 <div class="masthead__menu"> 115 <nav id="site-nav" class="greedy-nav" aria-label="Primary navigation"> 116 117 <a class="site-title" href="/"> 118 CAVA Lab 119 <span class="site-subtitle">Clinical AI Value Alignment</span> 120 </a> 121 <ul class="visible-links"><li class="masthead__menu-item"> 122 <a 123 href="/members" 124 125 126 >Members</a> 127 </li><li class="masthead__menu-item"> 128 <a 129 href="/research" 130 131 132 >Research</a> 133 </li><li class="masthead__menu-item"> 134 <a 135 href="/papers" 136 137 138 >Papers</a> 139 </li><li class="masthead__menu-item"> 140 <a 141 href="/posts" 142 143 144 >Posts</a> 145 </li><li class="masthead__menu-item"> 146 <a 147 href="/join" 148 149 150 >Join</a> 151 </li></ul> 152 153 <button class="greedy-nav__toggle hidden" type="button"> 154 <span class="visually-hidden">Toggle menu</span> 155 <div class="navicon"></div> 156 </button> 157 <ul class="hidden-links hidden"></ul> 158 </nav> 159 </div> 160 </div> 161</div> 162 163 164 <div class="initial-content"> 165 166 167 168 169 170 171<div id="main" role="main"> 172 173 174 <div class="sidebar sticky"> 175 176 177 178 179<div itemscope itemtype="https://schema.org/Person" class="h-card"> 180 181 182 <div class="author__avatar"> 183 <a href="https://cavalab.github.io/"> 184 <img src="/assets/images/space_bot3.jpg" alt="" itemprop="image" class="u-photo"> 185 </a> 186 </div> 187 188 189 <div class="author__content"> 190 <h3 class="author__name p-name" itemprop="name"> 191 <a class="u-url" rel="me" href="https://cavalab.github.io/" itemprop="url"></a> 192 </h3> 193 194 </div> 195 196 <div class="author__urls-wrapper"> 197 <button class="btn btn--inverse">Follow</button> 198 <ul class="author__urls social-icons"> 199 200 <li itemprop="homeLocation" itemscope itemtype="https://schema.org/Place"> 201 <i class="fas fa-fw fa-location-dot" aria-hidden="true"></i> <span itemprop="name" class="p-locality">Boston, MA</span> 202 </li> 203 204 205 206 207 208 <li><a href="mailto:[email protected]" rel="nofollow noopener noreferrer me"><i class="fas fa-fw fa-envelope" aria-hidden="true"></i><span class="label">Email</span></a></li> 209 210 211 212 <li><a href="https://github.com/cavalab" rel="nofollow noopener noreferrer me" itemprop="sameAs"><i class="fab fa-fw fa-github" aria-hidden="true"></i><span class="label">GitHub</span></a></li> 213 214 215 216 <li><a href="https://scholar.google.com/citations?user=iZB7inEAAAAJ&hl=en" rel="nofollow noopener noreferrer me" itemprop="sameAs"><i class="fas fa-graduation-cap" aria-hidden="true"></i><span class="label">Google Scholar</span></a></li> 217 218 219 220 <li><a href="https://connects.catalyst.harvard.edu/Profiles/display/Person/200560" rel="nofollow noopener noreferrer me" itemprop="sameAs"><i class="fas fa-project-diagram" aria-hidden="true"></i><span class="label">Harvard Catalyst</span></a></li> 221 222 223 224 <li><a href="http://chip.org" rel="nofollow noopener noreferrer me" itemprop="sameAs"><i class="fa fa-heartbeat" aria-hidden="true"></i><span class="label">CHIP</span></a></li> 225 226 227 228 <li><a href="https://www.childrenshospital.org/" rel="nofollow noopener noreferrer me" itemprop="sameAs"><i class="fa fa-medkit" aria-hidden="true"></i><span class="label">Boston Children's Hospital</span></a></li> 229 230 231 232 <li><a href="https://hms.harvard.edu/" rel="nofollow noopener noreferrer me" itemprop="sameAs"><i class="fa fa-university" aria-hidden="true"></i><span class="label">
232Harvard Medical School</span></a></li> 233 234 235 236 <li><a href="https://bsky.app/profile/lacava.bsky.social" rel="nofollow noopener noreferrer me" itemprop="sameAs"><i class="far fa-comment" aria-hidden="true"></i><span class="label">Bluesky</span></a></li> 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 <!-- 290 <li> 291 <a href="http://link-to-whatever-social-network.com/user/" itemprop="sameAs" rel="nofollow noopener noreferrer me"> 292 <i class="fas fa-fw" aria-hidden="true"></i> Custom Social Profile Link 293 </a> 294 </li> 295--> 296 </ul> 297 </div> 298</div> 299 300 301 302 </div> 303 304 305 306 <div class="archive"> 307 308 <h1 id="page-title" class="page__title">Papers</h1> 309 310 <hr /> 311 312<div class="pubitem"> 313 <div class="pubtitle" id="aldeiaguilhermeDeepTimetoEventModels"> 314 Deep Time-to-Event Models for Intrapartum Fetal Monitoring 315 </div> 316 <div class="pubauthors"> 317 318 319 320 321 322 323 Guilherme S. Imai Aldeia, 324 325 326 327 Helena Coggan, 328 329 330 331 Yuting Yang, 332 333 334 335 Lisa Levine, 336 337 338 339 Jennifer A. McCoy, 340 341 342 343 William G. La Cava 344 345 (2026) 346 </div> 347 348 349 350 351 352 <div class="pubinfo"> 353 Preprint 354 </div> 355 356 <div class="publinks"> 357 358 359 360 361 362 363 364 365 366 367 368 369 <a href="/assets/papers/Aldeia et al. - 2026 - Deep Time-to-Event Models for Intrapartum Fetal Mo.pdf">pdf</a> 370 371 372 </div> 373</div> 374 375<div class="pubitem"> 376 <div class="pubtitle" id="huPretrainFinetuneFramework2026"> 377 A pre-train and fine-tune framework for adaptive boosting of pre-trained polygenic risk scores 378 </div> 379 <div class="pubauthors"> 380 381 382 383 384 385 386 Jie Hu, 387 388 389 390 Raelynn Chen, 391 392 393 394 Maxwell Salvatore, 395 396 397 398 Olivia Wu, 399 400 401 402 Okan Bilge Ozdemir, 403 404 405 406 Yiwen Lu, 407 408 409 410 Shawn N. Murphy, 411 412 413 414 Elizabeth W. Karlson, 415 416 417 418 Atlas Khan, 419 420 421 422 Krzysztof Kiryluk, 423 424 425 426 Iftikhar J. Kullo, 427 428 429 430 Johanna L. Smith, 431 432 433 434 Eimear E. Kenny, 435 436 437 438 Yuan Luo, 439 440 441 442 Zaldy S. Tan, 443 444 445 446 William G. La Cava, 447 448 449 450 Marylyn D. Ritchie, 451 452 453 454 Yong Chen, 455 456 457 458 Ruowang Li 459 460 (2026) 461 </div> 462 463 464 465 466 467 <div class="pubjournal"> 468 Nature Communications 469 </div> 470 471 <div class="publinks"> 472 473 474 475 476 477 <a href="https://www.nature.com/articles/s41467-026-77128-5"><i class="fas fa-external-link-alt"></i> nature.com </a> 478 479 480 481 482 483 484 485 486 | 487 488 <a href="/assets/papers/Hu et al. - 2026 - A pre-train and fine-tune framework for adaptive b.pdf">pdf</a> 489 490 491 </div> 492</div> 493 494<div class="pubitem"> 495 <div class="pubtitle" id="aldeiaFoundationmodelApproachPediatric2026"> 496 A foundation-model approach to pediatric headache classification from rs-fMRI 497 </div> 498 <div class="pubauthors"> 499 500 501 502 503 504 505 Guilherme S. Imai Aldeia, 506 507 508 509 Clara Moon, 510 511 512 513 Julie Shulman, 514 515 516 517 Navil Sethna, 518 519 520 521 Allison Smith, 522 523 524 525 Alyssa Lebel, 526 527 528 529 William G. La Cava, 530 531 532 533 Scott Holmes 534 535 (2026) 536 </div> 537 538 539 540 541 542 <div class="pubjournal"> 543 Machine Learning for Healthcare Conference 544 </div> 545 546 <div class="publinks"> 547 548 549 550 551 552 <a href="http://arxiv.org/abs/2608.07287"><i class="fas fa-external-link-alt"></i> arxiv.org </a> 553 554 555 556 557 558 559 560 561 | 562 563 <a href="/assets/papers/Aldeia et al. - 2026 - A foundation-model approach to pediatric headache.pdf">pdf</a> 564 565 566 567 568 569 570 571 572 | In press 573 574 575 576 </div> 577</div> 578 579<div class="pubitem"> 580 <div class="pubtitle" id="mayourianSingleLeadElectrocardiographic2026"> 581 Single lead electrocardiographic detection of left ventricular systolic dysfunction in pediatric and congenital heart disease 582 </div> 583 <div class="pubauthors"> 584 585 586 587 588 589 590 Joshua Mayourian, 591 592 593 594 Ivor B. Asztalos, 595 596 597 598 William La Cava, 599 600 601 602 Ryan L. Kobayashi, 603 604 605 606 Sunil J. Ghelani, 607 608 609 610 Victoria L. Vetter, 611 612 613 614 Rachel M. Wald, 615 616 617 618 Anne Marie Valente, 619 620 621 622 Tal Geva, 623 624 625 626 John K. Triedman 627 628 (2026) 629 </div> 630 631 632 633 634 635 <div class="pubjournal"> 636 npj Digital Medicine 637 </div> 638 639 <div class="publinks"> 640 641 642 643 644 645 <a href="https://www.nature.com/articles/s41746-026-02646-x"><i class="fas fa-external-link-alt"></i> nature.com </a> 646 647 648 649 650 651 652 653 654 | 655 656 <a href="/assets/papers/Mayourian et al. - 2026 - Single lead electrocardiographic detection of left.pdf">pdf</a> 657 658 659 </div> 660</div> 661 662<div class="pubitem"> 663 <div class="pubtitle" id="reisDesignPrinciplesIntegrated2026"> 664 Design principles for integrated AI alignment 665 </div> 666 <div class="pubauthors"> 667 668 669 670 671 672 673 Ben Y. Reis and 674 675 676 677 William G. La Cava 678 679 (2026) 680 </div> 681 682 683 684 685 686 <div class="pubjournal"> 687 Patterns 688 </div> 689 690 <div class="publinks"> 691 692 693 694 695 696 <a href="https://www.cell.com/patterns/abstract/S2666-3899(26)00096-6"><i class="fas fa-external-link-alt"></i> cell.com </a> 697 698 699 700 | 701 <a href="http://arxiv.org/abs/2508.06592">arXiv</a> 702 703 704 705 706 707 708 | 709 710 <a href="/assets/papers/Reis and La Cava - 2026 - Design principles for integrated AI alignment.pdf">pdf</a> 711 712 713 </div> 714</div> 715 716<div class="pubitem"> 717 <div class="pubtitle" id="lukyanenkoEstimationLeftVentricular2026"> 718 Estimation of Left Ventricular Systolic Function in Pediatric and Congenital Heart Disease from Serial Electrocardiograms 719 </div> 720 <div class="pubauthors"> 721 722 723 724 725 726 727 Platon Lukyanenko, 728 729 730 731 Sunil J. Ghelani, 732 733 734 735 John K. Triedman, 736 737 738 739 Joshua Mayourian, 740 741 742 743 William G. La Cava 744 745 (2026) 746 </div> 747 748 749 750 751 752 <div class="pubjournal"> 753 AMIA Summits on Translational Science Proceedings 754 </div> 755 756 <div class="publinks"> 757 758 759 760 761 762 <a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC13274358/"><i class="fas fa-external-link-alt"></i> pmc.ncbi.nlm.nih.gov </a> 763 764 765 766 | 767 <a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC13274358/">PubMed</a> 768 769 770 771 772 773 774 | 775 776 <a href="/assets/papers/Lukyanenko et al. - 2026 - Estimation of Left Ventricular Systolic Function i.pdf">pdf</a> 777 778 779 </div> 780</div> 781 782<div class="pubitem"> 783 <div class="pubtitle" id="yangRobustAIECGPredicting2026"> 784 Robust AI-ECG for Predicting Left Ventricular Systolic Dysfunction in Pediatric Congenital Heart Disease 785 </div> 786 <div class="pubauthors"> 787 788 789 790 791 792 793 Yuting Yang, 794 795 796 797 Lorenzo Peracchio, 798 799 800 801 Joshua Mayourian, 802 803 804 805 John K. Triedman, 806 807 808 809 Timothy Miller, 810 811 812 813 William G. La Cava 814 815 (2026) 816 </div> 817 818 819 820 821 822 <div class="pubjournal"> 823 AMIA Summits on Translational Science Proceedings 824 </div> 825 826 <div class="publinks"> 827 828 829 830 831 832 <a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC13274275/"><i class="fas fa-external-link-alt"></i> pmc.ncbi.nlm.nih.gov </a> 833 834 835 836 | 837 <a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC13274275/">PubMed</a> 838 839 840 841 842 843 844 | 845 846 <a href="/assets/papers/Yang et al. - 2026 - Robust AI-ECG for Predicting Left Ventricular Syst.pdf">pdf</a> 847 848 849 </div> 850</div> 851 852<div class="pubitem"> 853 <div class="pubtitle" id="yangECGFoundationModel2026b"> 854 An ECG foundation model for generalizable cardiac function prediction across the lifespan 855 </div> 856 <div class="pubauthors"> 857 858 859 860 861 862 863 Yuting Yang, 864 865 866 867 Lorenzo Peracchio, 868 869 870 871 Joshua Mayourian, 872 873 874 875 Timothy Miller, 876 877 878 879 William G. La Cava 880 881 (2026) 882 </div> 883 884 885 886 887 888 <div class="pubjournal"> 889 medRxiv 890 </div> 891 892 <div class="publinks"> 893 894 895 896 897 898 <a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC13232360/"><i class="fas fa-external-link-alt"></i> pmc.ncbi.nlm.nih.gov </a> 899 900 901 902 903 904 905 906 907 | 908 909 <a href="/assets/papers/Yang et al. - 2026 - An ECG foundation model for generalizable cardiac.pdf">pdf</a> 910 911 912 </div> 913</div> 914 915<div class="pubitem">
916 <div class="pubtitle" id="lukyanenkoAutomatedEchocardiographicDetection2026a"> 917 Automated Echocardiographic Detection of Congenital Heart Disease Using Artificial Intelligence 918 </div> 919 <div class="pubauthors"> 920 921 922 923 924 925 926 Platon Lukyanenko, 927 928 929 930 Sunil J. Ghelani, 931 932 933 934 Yuting Yang, 935 936 937 938 Bohan Jiang, 939 940 941 942 Timothy A. Miller, 943 944 945 946 David Harrild, 947 948 949 950 Nao Sasaki, 951 952 953 954 Francesca Sperotto, 955 956 957 958 Danielle Sganga, 959 960 961 962 John K. Triedman, 963 964 965 966 Andrew J. Powell, 967 968 969 970 Tal Geva, 971 972 973 974 William G. La Cava, 975 976 977 978 Joshua Mayourian 979 980 (2026) 981 </div> 982 983 984 985 986 987 <div class="pubjournal"> 988 Circulation 989 </div> 990 991 <div class="publinks"> 992 993 994 995 996 997 <a href="https://www.ahajournals.org/doi/full/10.1161/CIRCULATIONAHA.126.079781"><i class="fas fa-external-link-alt"></i> ahajournals.org </a> 998 999 1000 1001 | 1002 <a href="https://pubmed.ncbi.nlm.nih.gov/41902792/">PubMed</a> 1003 1004 1005 1006 1007 1008 1009 | 1010 1011 <a href="/assets/papers/Lukyanenko et al. - 2026 - Automated Echocardiographic Detection of Congenita.pdf">pdf</a> 1012 1013 1014 </div> 1015</div> 1016 1017<div class="pubitem"> 1018 <div class="pubtitle" id="imaialdeiaSymbolicRegressionInterpretable2026"> 1019 Towards symbolic regression for interpretable clinical decision scores 1020 </div> 1021 <div class="pubauthors"> 1022 1023 1024 1025 1026 1027 1028 Guilherme Seidyo Imai Aldeia, 1029 1030 1031 1032 Joseph D. Romano, 1033 1034 1035 1036 Fabricio Olivetti de França, 1037 1038 1039 1040 Daniel S. Herman, 1041 1042 1043 1044 William G. La Cava 1045 1046 (2026) 1047 </div> 1048 1049 1050 1051 1052 1053 <div class="pubjournal"> 1054 Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 1055 </div> 1056 1057 <div class="publinks"> 1058 1059 1060 1061 1062 1063 <a href="https://royalsocietypublishing.org/rsta/article/384/2317/20240588/481208/Towards-symbolic-regression-for-interpretable"><i class="fas fa-external-link-alt"></i> royalsocietypublishing.org </a> 1064 1065 1066 1067 1068 1069 1070 1071 1072 | 1073 1074 <a href="/assets/papers/Imai Aldeia et al. - 2026 - Towards symbolic regression for interpretable clin.pdf">pdf</a> 1075 1076 1077 1078 1079 1080 1081 1082 1083 | 1084 <a href="https://github.com/cavalab/brush_paper_experiments">code</a> 1085 1086 1087 1088 </div> 1089</div> 1090 1091<div class="pubitem"> 1092 <div class="pubtitle" id="milaBenefitDoubtPhenomenon2026"> 1093 The Benefit of the Doubt Phenomenon in Emergency Triage Assignment Disparities 1094 </div> 1095 <div class="pubauthors"> 1096 1097 1098 1099 1100 1101 1102 Blanca Romero Mila, 1103 1104 1105 1106 Helena Coggan, 1107 1108 1109 1110 Andrew M. Fine, 1111 1112 1113 1114 Yuval Barak-Corren, 1115 1116 1117 1118 Ben Y. Reis, 1119 1120 1121 1122 Jaya Aysola, 1123 1124 1125 1126 Pradip Chaudhari, 1127 1128 1129 1130 William G. La Cava 1131 1132 (2026) 1133 </div> 1134 1135 1136 1137 1138 1139 <div class="pubinfo"> 1140 Preprint 1141 </div> 1142 1143 <div class="publinks"> 1144 1145 1146 1147 1148 1149 <a href="https://www.medrxiv.org/content/10.64898/2026.02.12.26346184v1"><i class="fas fa-external-link-alt"></i> medrxiv.org </a> 1150 1151 1152 1153 1154 1155 1156 1157 1158 | 1159 1160 <a href="/assets/papers/Mila et al. - 2026 - The Benefit of the Doubt Phenomenon in Emergency T.pdf">pdf</a> 1161 1162 1163 1164 1165 1166 1167 1168 1169 | 1170 <a href="https://github.com/cavalab/esi">
1170code</a> 1171 1172 1173 1174 </div> 1175</div> 1176 1177<div class="pubitem"> 1178 <div class="pubtitle" id="lukyanenkoDeepLearningBasedAutomated2026"> 1179 Deep Learning-Based Automated Echocardiographic Measurements in Pediatric and Congenital Heart Disease 1180 </div> 1181 <div class="pubauthors"> 1182 1183 1184 1185 1186 1187 1188 Platon Lukyanenko, 1189 1190 1191 1192 Sunil Ghelani, 1193 1194 1195 1196 Yuting Yang, 1197 1198 1199 1200 Bohan Jiang, 1201 1202 1203 1204 Timothy Miller, 1205 1206 1207 1208 Peter Higgins, 1209 1210 1211 1212 Manouk Kirakosian, 1213 1214 1215 1216 Kaitlyn Tracy, 1217 1218 1219 1220 Janet Kane, 1221 1222 1223 1224 David Harrild, 1225 1226 1227 1228 John Triedman, 1229 1230 1231 1232 Andrew J. Powell, 1233 1234 1235 1236 Tal Geva, 1237 1238 1239 1240 William La Cava, 1241 1242 1243 1244 Joshua Mayourian 1245 1246 (2026) 1247 </div> 1248 1249 1250 1251 1252 1253 <div class="pubinfo"> 1254 Preprint 1255 </div> 1256 1257 <div class="publinks"> 1258 1259 1260 1261 1262 1263 <a href="https://www.medrxiv.org/content/10.64898/2026.02.06.26345782v1"><i class="fas fa-external-link-alt"></i> medrxiv.org </a> 1264 1265 1266 1267 1268 1269 1270 1271 1272 | 1273 1274 <a href="/assets/papers/Lukyanenko et al. - 2026 - Deep Learning-Based Automated Echocardiographic Me.pdf">pdf</a> 1275 1276 1277 1278 1279 1280 1281 1282 1283 | 1284 <a href="https://echofocus.org">code</a> 1285 1286 1287 1288 </div> 1289</div> 1290 1291<div class="pubitem"> 1292 <div class="pubtitle" id="lukyanenkoDeepSurvivalAnalysis2025"> 1293 Deep survival analysis from adult and pediatric electrocardiograms: a multi-center benchmark study 1294 </div> 1295 <div class="pubauthors"> 1296 1297 1298 1299 1300 1301 1302 Platon Lukyanenko, 1303 1304 1305 1306 Joshua Mayourian, 1307 1308 1309 1310 Mingxuan Liu, 1311 1312 1313 1314 John K. Triedman, 1315 1316 1317 1318 Sunil J. Ghelani, 1319 1320 1321 1322 William G. La Cava 1323 1324 (2025) 1325 </div> 1326 1327 1328 1329 1330 1331 <div class="pubjournal"> 1332 BioData Mining 1333 </div> 1334 1335 <div class="publinks"> 1336 1337 1338 1339 1340 1341 <a href="https://doi.org/10.1186/s13040-025-00510-4"><i class="fas fa-external-link-alt"></i> doi.org </a> 1342 1343 1344 1345 | 1346 <a href="https://pubmed.ncbi.nlm.nih.gov/41408648/">PubMed</a> 1347 1348 1349 1350 1351 1352 1353 | 1354 1355 <a href="/assets/papers/Lukyanenko et al. - 2025 - Deep survival analysis from adult and pediatric el.pdf">pdf</a> 1356 1357 1358 </div> 1359</div> 1360 1361<div class="pubitem"> 1362 <div class="pubtitle" id="lacavaFutureAlgorithmicNondiscrimination2025"> 1363 The future of algorithmic nondiscrimination compliance in the affordable care act 1364 </div> 1365 <div class="pubauthors"> 1366 1367 1368 1369 1370 1371 1372 William G. La Cava, 1373 1374 1375 1376 I. Glenn Cohen, 1377 1378 1379 1380 Jaya Aysola 1381 1382 (2025) 1383 </div> 1384 1385 1386 1387 1388 1389 <div class="pubjournal"> 1390 npj Digital Medicine 1391 </div> 1392 1393 <div class="publinks"> 1394 1395 1396 1397 1398 1399 <a href="https://www.nature.com/articles/s41746-025-02224-7"><i class="fas fa-external-link-alt"></i> nature.com </a> 1400 1401 1402 1403 | 1404 <a href="https://pubmed.ncbi.nlm.nih.gov/41372617/">PubMed</a> 1405 1406 1407 1408 1409 1410 1411 | 1412 1413 <a href="/assets/papers/La Cava et al. - 2025 - The future of algorithmic nondiscrimination compli.pdf">pdf</a> 1414 1415 1416 1417 1418 1419 1420 1421 1422 | 1423 <a href="https://github.com/cavalab/aca-example">code</a> 1424 1425 1426 1427 </div> 1428</div> 1429 1430<div class="pubitem"> 1431 <div class="pubtitle" id="cogganDecipheringInfluenceDemographic2025"> 1432 Deciphering the influence of demographic factors on the treatment of pediatric patients in the emergency department 1433 </div> 1434 <div class="pubauthors"> 1435 1436 1437 1438 1439 1440 1441 Helena Coggan, 1442 1443 1444 1445 Anne Bischops, 1446 1447 1448 1449 Pradip Chaudhari, 1450 1451 1452 1453 Yuval Barak-Corren, 1454 1455 1456 1457 Andrew M. Fine, 1458 1459 1460 1461 Ben Y. Reis, 1462 1463 1464 1465 Jaya Aysola, 1466 1467 1468 1469 William G. La Cava 1470 1471 (2025) 1472 </div> 1473 1474 1475 1476 1477 1478 <div class="pubjournal"> 1479 Pacific Symposium on Biocomputing 1480 </div> 1481 1482 <div class="publinks"> 1483 1484 1485 1486 1487 1488 <a href="https://psb.stanford.edu/psb-online/proceedings/psb26/"><i class="fas fa-external-link-alt"></i> psb.stanford.edu </a> 1489 1490 1491 1492 | 1493 <a href="http://arxiv.org/abs/2510.02841">arXiv</a> 1494 1495 1496 1497 1498 1499 1500 | 1501 1502 <a href="/assets/papers/Coggan et al. - 2025 - Deciphering the influence of demographic factors o.pdf">pdf</a> 1503 1504 1505 1506 1507 1508 1509 1510 1511 | 1512 <a href="https://github.com/hcoggan/BCH-ED">
1512code</a> 1513 1514 1515 1516 1517 1518 1519 | 1520 <a href="https://cavalab.github.io//2025/10/24/ed-admissions.html">blog</a> 1521 1522 1523 1524 </div> 1525</div> 1526 1527<div class="pubitem"> 1528 <div class="pubtitle" id="liuEquitableSurvivalPrediction2025"> 1529 Equitable Survival Prediction: A Fairness-Aware Survival Modeling (FASM) Approach 1530 </div> 1531 <div class="pubauthors"> 1532 1533 1534 1535 1536 1537 1538 Mingxuan Liu, 1539 1540 1541 1542 Yilin Ning, 1543 1544 1545 1546 Haoyuan Wang, 1547 1548 1549 1550 Chuan Hong, 1551 1552 1553 1554 Matthew Engelhard, 1555 1556 1557 1558 Danielle S. Bitterman, 1559 1560 1561 1562 William G. La Cava, 1563 1564 1565 1566 Nan Liu 1567 1568 (2025) 1569 </div> 1570 1571 1572 1573 1574 1575 <div class="pubinfo"> 1576 Preprint 1577 </div> 1578 1579 <div class="publinks"> 1580 1581 1582 1583 1584 1585 <a href="http://arxiv.org/abs/2510.20629"><i class="fas fa-external-link-alt"></i> arxiv.org </a> 1586 1587 1588 1589 1590 1591 1592 1593 1594 | 1595 1596 <a href="/assets/papers/Liu et al. - 2025 - Equitable Survival Prediction A Fairness-Aware Su.pdf">pdf</a> 1597 1598 1599 </div> 1600</div> 1601 1602<div class="pubitem"> 1603 <div class="pubtitle" id="aldeiaIterativeLearningComputable2025"> 1604 Iterative Learning of Computable Phenotypes for Treatment Resistant Hypertension using Large Language Models 1605 </div> 1606 <div class="pubauthors"> 1607 1608 1609 1610 1611 1612 1613 Guilherme Seidyo Imai Aldeia, 1614 1615 1616 1617 Daniel S. Herman, 1618 1619 1620 1621 William La Cava 1622 1623 (2025) 1624 </div> 1625 1626 1627 1628 1629 1630 <div class="pubjournal"> 1631 Machine Learning for Healthcare Conference 1632 </div> 1633 1634 <div class="publinks"> 1635 1636 1637 1638 1639 1640 <a href="https://proceedings.mlr.press/v298/aldeia25a.html"><i class="fas fa-external-link-alt"></i> proceedings.mlr.press </a> 1641 1642 1643 1644 | 1645 <a href="http://arxiv.org/abs/2508.05581">arXiv</a> 1646 1647 1648 1649 1650 1651 1652 | 1653 1654 <a href="/assets/papers/Aldeia et al. - 2025 - Iterative Learning of Computable Phenotypes for Tr.pdf">pdf</a> 1655 1656 1657 1658 1659 1660 1661 1662 1663 | 1664 <a href="https://github.com/cavalab/htn-phenotyping-with-llms">code</a> 1665 1666 1667 1668 </div> 1669</div> 1670 1671<div class="pubitem"> 1672 <div class="pubtitle" id="imaialdeiaCallActionNext2025"> 1673 Call for Action: towards the next generation of symbolic regression benchmark 1674 </div> 1675 <div class="pubauthors"> 1676 1677 1678 1679 1680 1681 1682 Guilherme Seidyo Imai Aldeia, 1683 1684 1685 1686 Hengzhe Zhang, 1687 1688 1689 1690 Geoffrey Bomarito, 1691 1692 1693 1694 Miles Cranmer, 1695 1696 1697 1698 Alcides Fonseca, 1699 1700 1701 1702 Bogdan Burlacu, 1703 1704 1705 1706 William G. La Cava, 1707 1708 1709 1710 FabrÃcio Olivetti de França 1711 1712 (2025) 1713 </div> 1714 1715 1716 1717 1718 1719 <div class="pubjournal"> 1720 Proceedings of the Genetic and Evolutionary Computation Conference Companion 1721 </div> 1722 1723 <div class="publinks"> 1724 1725 1726 1727 1728 1729 <a href="https://dl.acm.org/doi/10.1145/3712255.37343
172909"><i class="fas fa-external-link-alt"></i> dl.acm.org </a> 1730 1731 1732 1733 | 1734 <a href="http://arxiv.org/abs/2505.03977">arXiv</a> 1735 1736 1737 1738 1739 1740 1741 | 1742 1743 <a href="/assets/papers/Imai Aldeia et al. - 2025 - Call for Action towards the next generation of sy.pdf">pdf</a> 1744 1745 1746 </div> 1747</div> 1748 1749<div class="pubitem"> 1750 <div class="pubtitle" id="ghelaniArtificialIntelligenceEnabledECG2025"> 1751 Artificial Intelligence-Enabled ECG to Detect Congenitally Corrected Transposition of the Great Arteries 1752 </div> 1753 <div class="pubauthors"> 1754 1755 1756 1757 1758 1759 1760 Sunil J. Ghelani, 1761 1762 1763 1764 Nikhil Thatte, 1765 1766 1767 1768 William La Cava, 1769 1770 1771 1772 John K. Triedman, 1773 1774 1775 1776 Joshua Mayourian 1777 1778 (2025) 1779 </div> 1780 1781 1782 1783 1784 1785 <div class="pubjournal"> 1786 Pediatric Cardiology 1787 </div> 1788 1789 <div class="publinks"> 1790 1791 1792 1793 1794 1795 <a href="https://link.springer.com/article/10.1007/s00246-025-03916-3"><i class="fas fa-external-link-alt"></i> link.springer.com </a> 1796 1797 1798 1799 1800 1801 1802 1803 1804 | 1805 1806 <a href="/assets/papers/Ghelani et al. - 2025 - Artificial Intelligence-Enabled ECG to Detect Cong.pdf">pdf</a> 1807 1808 1809 </div> 1810</div> 1811 1812<div class="pubitem"> 1813 <div class="pubtitle" id="gallifantReliabilityLargeLanguage2025"> 1814 Reliability of Large Language Model Knowledge Across Brand and Generic Cancer Drug Names 1815 </div> 1816 <div class="pubauthors"> 1817 1818 1819 1820 1821 1822 1823 Jack Gallifant, 1824 1825 1826 1827 Shan Chen, 1828 1829 1830 1831 Sandeep K. Jain, 1832 1833 1834 1835 Pedro Moreira, 1836 1837 1838 1839 Umit Topaloglu, 1840 1841 1842 1843 Hugo J.W.L. Aerts, 1844 1845 1846 1847 Jeremy L. Warner, 1848 1849 1850 1851 William G. La Cava, 1852 1853 1854 1855 Danielle S. Bitterman 1856 1857 (2025) 1858 </div> 1859 1860 1861 1862 1863 1864 <div class="pubjournal"> 1865 JCO Clinical Cancer Informatics 1866 </div> 1867 1868 <div class="publinks"> 1869 1870 1871 1872 1873 1874 <a href="https://ascopubs.org/doi/10.1200/CCI-24-00257"><i class="fas fa-external-link-alt"></i> ascopubs.org </a> 1875 1876 1877 1878 | 1879 <a href="https://pubmed.ncbi.nlm.nih.gov/40523223/">PubMed</a> 1880 1881 1882 1883 1884 1885 1886 | 1887 1888 <a href="/assets/papers/Gallifant et al. - 2025 - Reliability of Large Language Model Knowledge Acro.pdf">pdf</a> 1889 1890 1891 </div> 1892</div> 1893 1894<div class="pubitem"> 1895 <div class="pubtitle" id="lettIntersectionalMarginalDebiasing2025a"> 1896 Intersectional and Marginal Debiasing in Prediction Models for Emergency Admissions 1897 </div> 1898 <div class="pubauthors"> 1899 1900 1901 1902 1903 1904 1905 Elle Lett, 1906 1907 1908 1909 Shakiba Shahbandegan, 1910 1911 1912 1913 Yuval Barak-Corren, 1914 1915 1916 1917 Andrew M. Fine, 1918 1919 1920 1921 William G. La Cava 1922 1923 (2025) 1924 </div> 1925 1926 1927 1928 1929 1930 <div class="pubjournal"> 1931 JAMA Network Open 1932 </div> 1933 1934 <div class="publinks"> 1935 1936 1937 1938 1939 1940 <a href="https://doi.org/10.1001/jamanetworkopen.2025.12947"><i class="fas fa-external-link-alt"></i> doi.org </a> 1941 1942 1943 1944 | 1945 <a href="https://pmc.ncbi.nlm.nih.gov/articles/PMC12123471/">PubMed</a> 1946 1947 1948 1949 1950 1951 1952 | 1953 1954 <a href="/assets/papers/Lett et al. - 2025 - Intersectional and Marginal Debiasing in Predictio.pdf">pdf</a> 1955 1956 1957 1958 1959 1960 1961 1962 1963 | 1964 <a href="https://github.com/cavalab/marginal-intersectional">code</a> 1965 1966 1967 1968 </div> 1969</div> 1970 1971<div class="pubitem"> 1972 <div class="pubtitle" id="aldeiaApplicationArtificialNeural2025a"> 1973 Application of Artificial Neural Networks and Functional Brain Connectivity to Inform Pediatric Headache 1974 </div> 1975 <div class="pubauthors"> 1976 1977 1978 1979 1980 1981 1982 Guilherme Aldeia, 1983 1984 1985 1986 Clara Moon, 1987 1988 1989 1990 Julie Shulman, 1991 1992 1993 1994 Navil Sethna, 1995 1996 1997 1998 Allison Smith, 1999 2000 2001 2002 Alyssa Lebel, 2003 2004 2005 2006 William La Cava, 2007 2008 2009 2010 Scott Holmes 2011 2012 (2025) 2013 </div> 2014 2015 2016 2017 2018 2019 <div class="pubjournal"> 2020 The Journal of Pain 2021 </div> 2022 2023 <div class="publinks"> 2024 2025 2026 2027 2028 2029 <a href="https://www.jpain.org/article/S1526-5900(25)00366-9/abstract"><i class="fas fa-external-link-alt"></i> jpain.org </a> 2030 2031 2032 2033 2034 2035 2036 2037 2038 | 2039 2040 <a href="/assets/papers/Aldeia et al. - 2025 - Application of Artificial Neural Networks and Func.pdf">pdf</a> 2041 2042 2043 </div> 2044</div> 2045 2046<div class="pubitem"> 2047 <div class="pubtitle" id="mayourianElectrocardiogrambasedDeepLearning2025b"> 2048 Electrocardiogram-based deep learning to predict left ventricular systolic dysfunction in paediatric and adult congenital heart disease in the USA: a multicentre modelling study 2049 </div> 2050 <div class="pubauthors"> 2051 2052 2053 2054 2055 2056 2057 Joshua Mayourian, 2058 2059 2060 2061 Ivor B. Asztalos, 2062 2063 2064 2065 Amr El-Bokl, 2066 2067 2068 2069 Platon Lukyanenko, 2070 2071 2072 2073 Ryan L. Kobayashi, 2074 2075 2076 2077 William G. La Cava, 2078 2079 2080 2081 Sunil J. Ghelani, 2082 2083 2084 2085 Victoria L. Vetter, 2086 2087 2088 2089 John K. Triedman 2090 2091 (2025) 2092 </div> 2093 2094 2095 2096 2097 2098 <div class="pubjournal"> 2099 The Lancet Digital Health 2100 </div> 2101 2102 <div class="publinks"> 2103 2104 2105 2106 2107 2108 <a href="https://www.thelancet.com/journals/landig/article/PIIS2589-7500(25)00001-9/fulltext"><i class="fas fa-external-link-alt"></i> thelancet.com </a> 2109 2110 2111 2112 | 2113 <a href="https://pubmed.ncbi.nlm.nih.gov/40148010/">PubMed</a> 2114 2115 2116 2117 2118 2119 2120 | 2121
2122 <a href="/assets/papers/Mayourian et al. - 2025 - Electrocardiogram-based deep learning to predict l.pdf">pdf</a> 2123 2124 2125 </div> 2126</div> 2127 2128<div class="pubitem"> 2129 <div class="pubtitle" id="lacavaReviewSymbolicRegression2025"> 2130 A review of âSymbolic Regressionâ by Gabriel Kronberger, Bogdan Burlacu, Michael Kommenda, Stephan M. Winkler, and Michael Affenzeller, ISBN 978-1-138-05481-3, 2024, CRC Press. 2131 </div> 2132 <div class="pubauthors"> 2133 2134 2135 2136 2137 2138 2139 William G. La Cava 2140 2141 (2025) 2142 </div> 2143 2144 2145 2146 2147 2148 <div class="pubjournal"> 2149 Genetic Programming and Evolvable Machines 2150 </div> 2151 2152 <div class="publinks"> 2153 2154 2155 2156 2157 2158 <a href="https://doi.org/10.1007/s10710-025-09513-w"><i class="fas fa-external-link-alt"></i> doi.org </a> 2159 2160 2161 2162 2163 2164 2165 2166 2167 | 2168 2169 <a href="/assets/papers/La Cava - 2025 - A review of âSymbolic Regressionâ by Gabriel Kronb.pdf">pdf</a> 2170 2171 2172 </div> 2173</div> 2174 2175<div class="pubitem"> 2176 <div class="pubtitle" id="cogganDemographicFactorsAssociated2025"> 2177 Demographic Factors Associated with Triage Acuity, Admission and Length of Stay During Adult Emergency Department Visits 2178 </div> 2179 <div class="pubauthors"> 2180 2181 2182 2183 2184 2185 2186 Helena Coggan, 2187 2188 2189 2190 Pradip Chaudhari, 2191 2192 2193 2194 Yuval Barak-Corren, 2195 2196 2197 2198 Andrew M. Fine, 2199 2200 2201 2202 Ben Y. Reis, 2203 2204 2205 2206 Jaya Aysola, 2207 2208 2209 2210 William G. La Cava 2211 2212 (2025) 2213 </div> 2214 2215 2216 2217 2218 2219 <div class="pubinfo"> 2220 Preprint 2221 </div> 2222 2223 <div class="publinks"> 2224 2225 2226 2227 2228 2229 <a href="http://arxiv.org/abs/2503.22781"><i class="fas fa-external-link-alt"></i> arxiv.org </a> 2230 2231 2232 2233 2234 2235 2236 2237 2238 | 2239 2240 <a href="/assets/papers/Coggan et al. - 2025 - Demographic Factors Associated with Triage Acuity,.pdf">pdf</a> 2241 2242 2243 </div> 2244</div> 2245 2246<div class="pubitem"> 2247 <div class="pubtitle" id="mayourianExpertLevelAutomatedDiagnosis2025a"> 2248 Expert-Level Automated Diagnosis of the Pediatric ECG Using a Deep Neural Network 2249 </div> 2250 <div class="pubauthors"> 2251 2252 2253 2254 2255 2256 2257 Joshua Mayourian, 2258 2259 2260 2261 William G. La Cava, 2262 2263 2264 2265 Sarah D. de Ferranti, 2266 2267 2268 2269 Douglas Mah, 2270 2271 2272 2273 Mark Alexander, 2274 2275 2276 2277 Edward Walsh, 2278 2279 2280 2281 John K. Triedman 2282 2283 (2025) 2284 </div> 2285 2286 2287 2288 2289 2290 <div class="pubjournal"> 2291 JACC: Clinical Electrophysiology 2292 </div> 2293 2294 <div class="publinks"> 2295 2296 2297 2298 2299 2300 <a href="https://www.sciencedirect.com/science/article/pii/S2405500X25000829"><i class="fas fa-external-link-alt"></i> sciencedirect.com </a> 2301 2302 2303 2304 2305 2306 2307 2308 2309 | 2310 2311 <a href="/assets/papers/Mayourian et al. - 2025 - Expert-Level Automated Diagnosis of the Pediatric.pdf">pdf</a> 2312 2313 2314 </div> 2315</div> 2316 2317<div class="pubitem"> 2318 <div class="pubtitle" id="mayourianElectrocardiogrambasedDeepLearning2025c"> 2319 Electrocardiogram-based deep learning to predict mortality in paediatric and adult congenital heart disease 2320 </div> 2321 <div class="pubauthors"> 2322 2323 2324 2325 2326 2327 2328 Joshua Mayourian, 2329 2330 2331 2332 Amr El-Bokl, 2333 2334 2335 2336 Platon Lukyanenko, 2337 2338 2339 2340 William G. La Cava, 2341 2342 2343 2344 Tal Geva, 2345 2346 2347 2348 Anne Marie Valente, 2349 2350 2351 2352 John K Triedman, 2353 2354 2355 2356 Sunil J Ghelani 2357 2358 (2025) 2359 </div> 2360 2361 2362 2363 2364 2365 <div class="pubjournal"> 2366 European Heart Journal 2367 </div> 2368 2369 <div class="publinks"> 2370 2371 2372 2373 2374 2375 <a href="https://doi.org/10.1093/eurheartj/ehae651"><i class="fas fa-external-link-alt"></i> doi.org </a> 2376 2377 2378 2379 | 2380 <a href="https://pubmed.ncbi.nlm.nih.gov/39387652/">PubMed</a> 2381 2382 2383 2384 2385 2386 2387 | 2388
2389 <a href="/assets/papers/Mayourian et al. - 2025 - Electrocardiogram-based deep learning to predict m.pdf">pdf</a> 2390 2391 2392 </div> 2393</div> 2394 2395<div class="pubitem"> 2396 <div class="pubtitle" id="teeleInvestigationNovelNoninvasive2025"> 2397 Investigation of a Novel Noninvasive Risk Analytics Algorithm With Laboratory Central Venous Oxygen Saturation Measurements in Critically Ill Pediatric Patients 2398 </div> 2399 <div class="pubauthors"> 2400 2401 2402 2403 2404 2405 2406 Sarah A. Teele, 2407 2408 2409 2410 Avihu Z. Gazit, 2411 2412 2413 2414 Craig Futterman, 2415 2416 2417 2418 William G. La Cava, 2419 2420 2421 2422 David S. Cooper, 2423 2424 2425 2426 Steven M. Schwartz, 2427 2428 2429 2430 Joshua W. Salvin 2431 2432 (2025) 2433 </div> 2434 2435 2436 2437 2438 2439 <div class="pubjournal"> 2440 Critical Care Explorations 2441 </div> 2442 2443 <div class="publinks"> 2444 2445 2446 2447 2448 2449 <a href="https://journals.lww.com/10.1097/CCE.0000000000001204"><i class="fas fa-external-link-alt"></i> journals.lww.com </a> 2450 2451 2452 2453 2454 2455 2456 2457 2458 | 2459 2460 <a href="/assets/papers/Teele et al. - 2025 - Investigation of a Novel Noninvasive Risk Analytic.pdf">pdf</a> 2461 2462 2463 </div> 2464</div> 2465 2466<div class="pubitem"> 2467 <div class="pubtitle" id="chenCrossCareAssessingHealthcare2024"> 2468 Cross-Care: Assessing the Healthcare Implications of Pre-training Data on Language Model Bias 2469 </div> 2470 <div class="pubauthors"> 2471 2472 2473 2474 2475 2476 2477 Shan Chen, 2478 2479 2480 2481 Jack Gallifant, 2482 2483 2484 2485 Mingye Gao, 2486 2487 2488 2489 Pedro Moreira, 2490 2491 2492 2493 Nikolaj Munch, 2494 2495 2496 2497 Ajay Muthukkumar, 2498 2499 2500 2501 Arvind Rajan, 2502 2503 2504 2505 Jaya Kolluri, 2506 2507 2508 2509 Amelia Fiske, 2510 2511 2512 2513 Janna Hastings, 2514 2515 2516 2517 Hugo Aerts, 2518 2519 2520 2521 Brian Anthony, 2522 2523 2524 2525 Leo A. Celi, 2526 2527 2528 2529 William G. La Cava, 2530 2531 2532 2533 Danielle S. Bitterman 2534 2535 (2024) 2536 </div> 2537 2538 2539 2540 2541 2542 <div class="pubjournal"> 2543 Advances in Neural Information Processing Systems (NeurIPS) 2544 </div> 2545 2546 <div class="publinks"> 2547 2548 2549 2550 2551 2552 <a href="https://proceedings.neurips.cc/paper_files/paper/2024/hash/2a617efee5815f12b405d40569dea0a5-Abstract-Datasets_and_Benchmarks_Track.html"><i class="fas fa-external-link-alt"></i> proceedings.neurips.cc </a> 2553 2554 2555 2556 | 2557 <a href="http://arxiv.org/abs/2405.05506">arXiv</a> 2558 2559 2560 2561 2562 2563 2564 | 2565 2566 <a href="/assets/papers/Chen et al. - 2024 - Cross-Care Assessing the Healthcare Implications.pdf">pdf</a> 2567 2568 2569 </div> 2570</div> 2571 2572<div class="pubitem"> 2573 <div class="pubtitle" id="mayourianDeepLearningBasedElectrocardiogram2024a"> 2574 Deep Learning-Based Electrocardiogram Analysis Predicts Biventricular Dysfunction and Dilation in Congenital Heart Disease 2575 </div> 2576 <div class="pubauthors"> 2577 2578 2579 2580 2581 2582 2583 Joshua Mayourian, 2584 2585 2586 2587 Addison Gearhart, 2588 2589 2590 2591 William G. La Cava, 2592 2593 2594 2595 Akhil Vaid, 2596 2597 2598
2599 Girish N. Nadkarni, 2600 2601 2602 2603 John K. Triedman, 2604 2605 2606 2607 Andrew J. Powell, 2608 2609 2610 2611 Rachel M. Wald, 2612 2613 2614 2615 Anne Marie Valente, 2616 2617 2618 2619 Tal Geva, 2620 2621 2622 2623 Son Q. Duong, 2624 2625 2626 2627 Sunil J. Ghelani 2628 2629 (2024) 2630 </div> 2631 2632 2633 2634 2635 2636 <div class="pubjournal"> 2637 Journal of the American College of Cardiology 2638 </div> 2639 2640 <div class="publinks"> 2641 2642 2643 2644 2645 2646 <a href="https://linkinghub.elsevier.com/retrieve/pii/S0735109724076769"><i class="fas fa-external-link-alt"></i> linkinghub.elsevier.com </a> 2647 2648 2649 2650 | 2651 <a href="https://pubmed.ncbi.nlm.nih.gov/39168568/">PubMed</a> 2652 2653 2654 2655 2656 2657 2658 | 2659 2660 <a href="/assets/papers/Mayourian et al. - 2024 - Deep Learning-Based Electrocardiogram Analysis Pre.pdf">pdf</a> 2661 2662 2663 </div> 2664</div> 2665 2666<div class="pubitem"> 2667 <div class="pubtitle" id="aldeiaInexactSimplificationSymbolic2024"> 2668 Inexact Simplification of Symbolic Regression Expressions with Locality-sensitive Hashing 2669 </div> 2670 <div class="pubauthors"> 2671 2672 2673 2674 2675 2676 2677 Guilherme Seidyo Imai Aldeia, 2678 2679 2680 2681 Fabricio Olivetti de Franca, 2682 2683 2684 2685 William G. La Cava 2686 2687 (2024) 2688 </div> 2689 2690 2691 2692 2693 2694 <div class="pubjournal"> 2695 GECCO '24: Genetic and Evolutionary Computation Conference 2696 </div> 2697 2698 <div class="publinks"> 2699 2700 2701 2702 2703 2704 2705 <a href="http://arxiv.org/abs/2404.05898">arXiv</a> 2706 2707 2708 2709 2710 2711 2712 | 2713 2714 <a href="/assets/papers/Aldeia et al. - 2024 - Inexact Simplification of Symbolic Regression Expr.pdf">pdf</a> 2715 2716 2717 2718 2719 2720 2721 2722 2723 | 2724 <a href=" https://github.com/gAldeia/hashing-symbolic-expressions">code</a> 2725 2726 2727 2728 2729 2730 2731 | 2732 <a href="https://cavalab.github.io//2024/04/14/inexact-simplification.html">blog</a> 2733 2734 2735 2736 </div> 2737</div> 2738 2739<div class="pubitem"> 2740 <div class="pubtitle" id="aldeiaMinimumVarianceThreshold2024"> 2741 Minimum variance threshold for epsilon-lexicase selection 2742 </div> 2743 <div class="pubauthors"> 2744 2745 2746 2747 2748 2749 2750 Guilherme Seidyo Imai Aldeia, 2751 2752 2753 2754 FabrÃcio Olivetti De França, 2755 2756 2757 2758 William G. La Cava 2759 2760 (2024) 2761 </div> 2762 2763 2764 2765 2766 2767 <div class="pubjournal"> 2768 GECCO '24: Genetic and Evolutionary Computation Conference 2769 </div> 2770 2771 <div class="publinks"> 2772 2773 2774 2775 2776 2777 <a href="https://dl.acm.org/doi/10.1145/3638529.3654149"><i class="fas fa-external-link-alt"></i> dl.acm.org </a> 2778 2779 2780 2781 | 2782 <a href="https://arxiv.org/abs/2404.05909">arXiv</a> 2783 2784 2785 2786 2787 2788 2789 | 2790 2791 <a href="/assets/papers/Aldeia et al. - 2024 - Minimum variance threshold for epsilon-lexicase se.pdf">pdf</a> 2792 2793 2794 2795 2796 2797 2798 2799 2800 | 2801 <a href=" https://github.com/gAldeia/srbench/tree/feat_split_benchmark">code</a> 2802 2803 2804 2805 </div> 2806</div> 2807 2808<div class="pubitem"> 2809 <div class="pubtitle" id="defrancaSRBenchPrincipledBenchmarking2024"> 2810 SRBench++: Principled Benchmarking of Symbolic Regression With Domain-Expert Interpretation 2811 </div> 2812 <div class="pubauthors"> 2813 2814 2815 2816 2817 2818 2819 F. O. de Franca, 2820 2821 2822 2823 M. Virgolin, 2824 2825 2826 2827 M. Kommenda, 2828 2829 2830 2831 M. S. Majumder, 2832 2833 2834 2835 M. Cranmer, 2836 2837 2838 2839 G. Espada, 2840 2841 2842 2843 L. Ingelse, 2844 2845 2846 2847 A. Fonseca, 2848 2849 2850 2851 M. Landajuela, 2852 2853 2854 2855 B. Petersen, 2856 2857 2858 2859 R. Glatt, 2860 2861 2862 2863 N. Mundhenk, 2864 2865 2866 2867 C. S. Lee, 2868 2869 2870 2871 J. D. Hochhalter, 2872 2873 2874 2875 D. L. Randall, 2876 2877 2878 2879 P. Kamienny, 2880 2881 2882 2883 H. Zhang, 2884 2885 2886 2887 G. Dick, 2888 2889 2890 2891 A. Simon, 2892 2893 2894 2895 B. Burlacu, 2896 2897 2898 2899 Jaan Kasak, 2900 2901 2902 2903 Meera Machado, 2904 2905 2906 2907 Casper Wilstrup, 2908 2909 2910 2911 W. G. La Cava 2912 2913 (2024) 2914 </div> 2915 2916 2917 2918 2919 2920 <div class="pubjournal"> 2921 IEEE Transactions on Evolutionary Computation 2922 </div> 2923 2924 <div class="publinks"> 2925 2926 2927 2928 2929 2930 <a href="https://ieeexplore.ieee.org/document/10586218/?arnumber=10586218"><i class="fas fa-external-link-alt"></i> ieeexplore.ieee.org </a> 2931 2932 2933 2934 | 2935 <a href="https://arxiv.org/abs/2304.01117">arXiv</a> 2936 2937 2938 2939 2940 2941 2942 | 2943 2944 <a href="/assets/papers/de Franca et al. - 2024 - SRBench++ Principled Benchmarking of Symbolic Reg.pdf">pdf</a> 2945 2946 2947 2948 2949 2950 2951 2952 2953 | 2954 <a href="https://cavalab.org/srbench">
2954code</a> 2955 2956 2957 2958 </div> 2959</div> 2960 2961<div class="pubitem"> 2962 <div class="pubtitle" id="mayourianPediatricElectrocardiogramBasedDeep2024"> 2963 Pediatric Electrocardiogram-Based Deep Learning to Predict Secundum Atrial Septal Defects 2964 </div> 2965 <div class="pubauthors"> 2966 2967 2968 2969 2970 2971 2972 Joshua Mayourian, 2973 2974 2975 2976 Robert Geggel, 2977 2978 2979 2980 William G. La Cava, 2981 2982 2983 2984 Sunil J. Ghelani, 2985 2986 2987 2988 John K. Triedman 2989 2990 (2024) 2991 </div> 2992 2993 2994 2995 2996 2997 <div class="pubjournal"> 2998 Pediatric Cardiology 2999 </div> 3000 3001 <div class="publinks"> 3002 3003 3004 3005 3006 3007 <a href="https://doi.org/10.1007/s00246-024-03540-7"><i class="fas fa-external-link-alt"></i> doi.org </a> 3008 3009 3010 3011 3012 3013 3014 3015 3016 | 3017 3018 <a href="/assets/papers/Mayourian et al. - 2024 - Pediatric Electrocardiogram-Based Deep Learning to.pdf">pdf</a> 3019 3020 3021 </div> 3022</div> 3023 3024<div class="pubitem"> 3025 <div class="pubtitle" id="mccoyIntrapartumElectronicFetal2024"> 3026 Intrapartum electronic fetal heart rate monitoring to predict acidemia at birth with the use of deep learning 3027 </div> 3028 <div class="pubauthors"> 3029 3030 3031 3032 3033 3034 3035 Jennifer A. McCoy, 3036 3037 3038 3039 Lisa D. Levine, 3040 3041 3042 3043 Guangya Wan, 3044 3045 3046 3047 Corey Chivers, 3048 3049 3050 3051 Joseph Teel, 3052 3053 3054 3055 William G. La Cava 3056 3057 (2024) 3058 </div> 3059 3060 3061 3062 3063 3064 <div class="pubjournal"> 3065 American Journal of Obstetrics and Gynecology (AJOG) 3066 </div> 3067 3068 <div class="publinks"> 3069 3070 3071 3072 3073 3074 <a href="https://www.sciencedirect.com/science/article/pii/S0002937824005283"><i class="fas fa-external-link-alt"></i> sciencedirect.com </a> 3075 3076 3077 3078 | 3079 <a href="https://pubmed.ncbi.nlm.nih.gov/38663662/">PubMed</a> 3080 3081 3082 3083 3084 3085 3086 | 3087 3088 <a href="/assets/papers/McCoy et al. - 2024 - Intrapartum electronic fetal heart rate monitoring.pdf">pdf</a> 3089 3090 3091 3092 3093 3094 3095 3096 3097 | 3098 <a href="https://github.com/cavalab/ai-efm">code</a> 3099 3100 3101 3102 </div> 3103</div> 3104 3105<div class="pubitem"> 3106 <div class="pubtitle" id="mayourianDeepLearningbasedElectrocardiogram2024"> 3107 Deep learning-based electrocardiogram analysis to predict biventricular dysfunction and dilation in congenital heart disease 3108 </div> 3109 <div class="pubauthors"> 3110 3111 3112 3113 3114 3115 3116 Joshua Mayourian, 3117 3118 3119 3120 Addison Gearhart, 3121 3122 3123 3124 William G La Cava, 3125 3126 3127 3128 John K. Triedman, 3129 3130 3131 3132 Andrew J. Powell, 3133 3134 3135 3136 Anne Marie Valente, 3137 3138 3139 3140 Tal Geva, 3141 3142 3143 3144 Sunil J. Ghelani 3145 3146 (2024) 3147 </div> 3148 3149 3150 3151 3152 3153 <div class="pubjournal"> 3154 Journal of the American College of Cardiology (JACC) 3155 </div> 3156 3157 <div class="publinks"> 3158 3159 3160 3161 3162 3163 <a href="https://www.jacc.org/doi/full/10.1016/S0735-1097%2824%2903587-3"><i class="fas fa-external-link-alt"></i> jacc.org </a> 3164 3165 3166 3167 3168 3169 3170 3171 3172 | 3173 3174 <a href="/assets/papers/Mayourian et al. - 2024 - Deep learning-based electrocardiogram analysis to.pdf">pdf</a> 3175 3176 3177 </div> 3178</div> 3179 3180<div class="pubitem"> 3181 <div class="pubtitle" id="mccoyAccuracyDeepLearning2024a"> 3182 Accuracy of deep learning models in interpreting intrapartum fetal monitoring to predict fetal acidemia 3183 </div> 3184 <div class="pubauthors"> 3185 3186 3187 3188 3189 3190 3191 Jennifer A. McCoy, 3192 3193 3194 3195 Guangya Wan, 3196 3197 3198 3199 Lisa D. Levine, 3200 3201 3202 3203 Joseph Teel, 3204 3205 3206 3207 John Holmes, 3208 3209 3210 3211 William G. La Cava 3212 3213 (2024) 3214 </div> 3215 3216 3217 3218 3219 3220 <div class="pubjournal"> 3221 American Journal of Obstetrics and Gynecology 3222 </div> 3223 3224 <div class="publinks"> 3225 3226 3227 3228 3229 3230 <a href="https://linkinghub.elsevier.com/retrieve/pii/S0002937823010694"><i class="fas fa-external-link-alt"></i> linkinghub.elsevier.com </a> 3231 3232 3233 3234 3235 3236 3237 3238 3239 | 3240 3241 <a href="/assets/papers/McCoy et al. - 2024 - Accuracy of deep learning models in interpreting i.pdf">pdf</a> 3242 3243 3244 </div> 3245</div> 3246 3247<div class="pubitem"> 3248 <div class="pubtitle" id="rodriguesExploringSLUGFeature2023"> 3249 Exploring SLUG: Feature Selection Using Genetic Algorithms and Genetic Programming 3250 </div> 3251 <div class="pubauthors"> 3252 3253 3254 3255 3256 3257 3258 Nuno M. Rodrigues, 3259 3260 3261 3262 João E. Batista, 3263 3264 3265 3266 William G La Cava, 3267 3268 3269 3270 Leonardo Vanneschi, 3271 3272 3273 3274 Sara Silva 3275 3276 (2023) 3277 </div> 3278 3279 3280 3281 3282 3283 <div class="pubjournal"> 3284 SN Computer Science 3285 </div> 3286 3287 <div class="publinks"> 3288 3289 3290 3291 3292 3293 <a href="https://doi.org/10.1007/s42979-023-02106-3"><i class="fas fa-external-link-alt"></i> doi.org </a> 3294 3295 3296 3297 3298 3299 3300 3301 3302 | 3303 3304 <a href="/assets/papers/Rodrigues et al. - 2023 - Exploring SLUG Feature Selection Using Genetic Al.pdf">pdf</a> 3305 3306 3307 </div> 3308</div> 3309 3310<div class="pubitem">
3311 <div class="pubtitle" id="poteatEffectsRaceGender2023"> 3312 Effects of Race and Gender Classifications on Atherosclerotic Cardiovascular Disease Risk Estimates for Clinical Decision-Making in a Cohort of Black Transgender Women 3313 </div> 3314 <div class="pubauthors"> 3315 3316 3317 3318 3319 3320 3321 Tonia Poteat, 3322 3323 3324 3325 Elle Lett, 3326 3327 3328 3329 Ashleigh J. Rich, 3330 3331 3332 3333 Huijun Jiang, 3334 3335 3336 3337 Andrea L. Wirtz, 3338 3339 3340 3341 Asa Radix, 3342 3343 3344 3345 Sari L. Reisner, 3346 3347 3348 3349 Alexander B. Harris, 3350 3351 3352 3353 Jowanna Malone, 3354 3355 3356 3357 William G. La Cava, 3358 3359 3360 3361 Catherine R. Lesko, 3362 3363 3364 3365 Kenneth H. Mayer, 3366 3367 3368 3369 Carl G. Streed 3370 3371 (2023) 3372 </div> 3373 3374 3375 3376 3377 3378 <div class="pubjournal"> 3379 Health Equity 3380 </div> 3381 3382 <div class="publinks"> 3383 3384 3385 3386 3387 3388 <a href="https://www.liebertpub.com/doi/10.1089/heq.2023.0066"><i class="fas fa-external-link-alt"></i> liebertpub.com </a> 3389 3390 3391 3392 3393 3394 3395 3396 3397 | 3398 3399 <a href="/assets/papers/Poteat et al. - 2023 - Effects of Race and Gender Classifications on Athe.pdf">pdf</a> 3400 3401 3402 </div> 3403</div> 3404 3405<div class="pubitem"> 3406 <div class="pubtitle" id="lacavaFairAdmissionRisk2023b"> 3407 Fair admission risk prediction with proportional multicalibration 3408 </div> 3409 <div class="pubauthors"> 3410 3411 3412 3413 3414 3415 3416 William G. La Cava, 3417 3418 3419 3420 Elle Lett, 3421 3422 3423 3424 Guangya Wan 3425 3426 (2023) 3427 </div> 3428 3429 3430 3431 3432 3433 <div class="pubjournal"> 3434 Conference on Health, Inference, and Learning 3435 </div> 3436 3437 <div class="publinks"> 3438 3439 3440 3441 3442 3443 <a href="https://proceedings.mlr.press/v209/la-cava23a.html"><i class="fas fa-external-link-alt"></i> proceedings.mlr.press </a> 3444 3445 3446 3447 3448 3449 3450 3451 3452 | 3453 3454 <a href="/assets/papers/La Cava et al. - 2023 - Fair admission risk prediction with proportional m.pdf">pdf</a> 3455 3456 3457 3458 3459 3460 3461 3462 3463 | 3464 <a href="https://github.com/cavalab/pmcboost">code</a> 3465 3466 3467 3468 3469 3470 3471 | 3472 <i class="fas fa-trophy"></i> 3473 Best Paper Award 3474 3475 3476 3477 </div> 3478</div> 3479 3480<div class="pubitem"> 3481 <div class="pubtitle" id="lacavaFlexibleSymbolicRegression2023a"> 3482 A flexible symbolic regression method for constructing interpretable clinical prediction models 3483 </div> 3484 <div class="pubauthors"> 3485 3486 3487 3488 3489 3490 3491 William G. La Cava, 3492 3493 3494 3495 Paul C. Lee, 3496 3497 3498 3499 Imran Ajmal, 3500 3501 3502 3503 Xiruo Ding, 3504 3505 3506 3507 Priyanka Solanki, 3508 3509 3510 3511 Jordana B. Cohen, 3512 3513 3514 3515 Jason H. Moore, 3516 3517 3518 3519 Daniel S. Herman 3520 3521 (2023) 3522 </div> 3523 3524 3525 3526 3527 3528 <div class="pubjournal"> 3529 npj Digital Medicine 3530 </div> 3531 3532 <div class="publinks"> 3533 3534 3535 3536 3537 3538 <a href="https://www.nature.com/articles/s41746-023-00833-8"><i class="fas fa-external-link-alt"></i> nature.com </a> 3539 3540 3541 3542 | 3543 <a href="https://www.medrxiv.org/content/10.1101/2020.12.12.20248005v2">medRxiv</a> 3544 3545 3546 3547 3548 3549 3550 | 3551 3552 <a href="/assets/papers/La Cava et al. - 2023 - A flexible symbolic regression method for construc.pdf">pdf</a> 3553 3554 3555 3556 3557 3558 3559 3560 3561 | 3562 <a href="https://github.com/cavalab/feat">code</a> 3563 3564 3565 3566 3567 3568 3569 | 3570 <i class="fas fa-trophy"></i> 3571 HUMIES Silver Medal 3572 3573 3574 3575 3576 3577 3578 <a href="https://www.human-competitive.org/awards"><i class="fas fa-external-link-alt"></i> </a> 3579 3580 3581 3582 3583 3584 3585 | 3586 <a href="https://cavalab.github.io/2023/09/02/humies.html">blog</a> 3587 3588 3589 3590 </div> 3591</div> 3592 3593<div class="pubitem"> 3594 <div class="pubtitle" id="lettTranslatingIntersectionalityFair2023a"> 3595 Translating intersectionality to fair machine learning in health sciences 3596 </div> 3597 <div class="pubauthors"> 3598 3599 3600 3601 3602 3603 3604 Elle Lett and 3605 3606 3607 3608 William G. La Cava 3609 3610 (2023) 3611 </div> 3612 3613 3614 3615 3616 3617 <div class="pubjournal"> 3618 Nature Machine Intelligence 3619 </div> 3620 3621 <div class="publinks"> 3622 3623 3624 3625 3626 3627 <a href="https://www.nature.com/articles/s42256-023-00651-3"><i class="fas fa-external-link-alt"></i> nature.com </a> 3628 3629 3630 3631 3632 3633 3634 3635 3636 | 3637 3638 <a href="/assets/papers/Lett and La Cava - 2023 - Translating intersectionality to fair machine lear.pdf">pdf</a> 3639 3640 3641 3642 3643 3644 3645 3646 3647 | 3648 <a href="https://cavalab.github.io/2023/05/05/intersectionality.html">blog</a> 3649 3650 3651 3652 </div> 3653</div> 3654 3655<div class="pubitem"> 3656 <div class="pubtitle" id="lacavaOptimizingFairnessTradeoffs2023a"> 3657 Optimizing fairness tradeoffs in machine learning with multiobjective meta-models 3658 </div> 3659 <div class="pubauthors"> 3660 3661 3662 3663 3664 3665 3666 William G. La Cava 3667 3668 (2023) 3669 </div> 3670 3671 3672 3673 3674 3675 <div class="pubjournal"> 3676 GECCO '23 3677 </div> 3678 3679 <div class="publinks"> 3680 3681 3682 3683 3684 3685 <a href="https://dl.acm.org/doi/10.1145/3583131.3590487"><i class="fas fa-external-link-alt"></i> dl.acm.org </a> 3686 3687 3688 3689 | 3690 <a href="http://arxiv.org/abs/2304.12190">arXiv</a> 3691 3692 3693 3694 3695 3696 3697 | 3698 3699 <a href="/assets/papers/La Cava - 2023 - Optimizing fairness tradeoffs in machine learning.pdf">pdf</a> 3700 3701 3702 3703 3704 3705 3706 3707 3708 | 3709 <a href="https://cavalab.org/fomo">
3709code</a> 3710 3711 3712 3713 </div> 3714</div> 3715 3716<div class="pubitem"> 3717 <div class="pubtitle" id="tanInformativeMissingnessWhat2023"> 3718 Informative missingness: What can we learn from patterns in missing laboratory data in the electronic health record? 3719 </div> 3720 <div class="pubauthors"> 3721 3722 3723 3724 3725 3726 3727 Amelia L. M. Tan, 3728 3729 3730 3731 Emily J. Getzen, 3732 3733 3734 3735 Meghan R. Hutch, 3736 3737 3738 3739 Zachary H. Strasser, 3740 3741 3742 3743 Alba Gutiérrez-Sacristán, 3744 3745 3746 3747 Trang T. Le, 3748 3749 3750 3751 Arianna Dagliati, 3752 3753 3754 3755 Michele Morris, 3756 3757 3758 3759 David A. Hanauer, 3760 3761 3762 3763 Bertrand Moal, 3764 3765 3766 3767 Clara-Lea Bonzel, 3768 3769 3770 3771 William Yuan, 3772 3773 3774 3775 Lorenzo Chiudinelli, 3776 3777 3778 3779 Priam Das, 3780 3781 3782 3783 Harrison G. Zhang, 3784 3785 3786 3787 Bruce J. Aronow, 3788 3789 3790 3791 Paul Avillach, 3792 3793 3794 3795 Gabriel. A. Brat, 3796 3797 3798 3799 Tianxi Cai, 3800 3801 3802 3803 Chuan Hong, 3804 3805 3806 3807 William G. La Cava, 3808 3809 3810 3811 He Hooi Will Loh, 3812 3813 3814 3815 Yuan Luo, 3816 3817 3818 3819 Shawn N. Murphy, 3820 3821 3822 3823 Kee Yuan Hgiam, 3824 3825 3826 3827 Gilbert S. Omenn, 3828 3829 3830 3831 Lav P. Patel, 3832 3833 3834 3835 Malarkodi Jebathilagam Samayamuthu, 3836 3837 3838 3839 Emily R. Shriver, 3840 3841 3842 3843 Zahra Shakeri Hossein Abad, 3844 3845 3846 3847 Byorn W. L. Tan, 3848 3849 3850 3851 Shyam Visweswaran, 3852 3853 3854 3855 Xuan Wang, 3856 3857 3858 3859 Griffin M. Weber, 3860 3861 3862 3863 Zongqi Xia, 3864 3865 3866 3867 Bertrand Verdy, 3868 3869 3870 3871 Qi Long, 3872 3873 3874 3875 Danielle L. Mowery, 3876 3877 3878 3879 John H. Holmes 3880 3881 (2023) 3882 </div> 3883 3884 3885 3886 3887 3888 <div class="pubjournal"> 3889 Journal of Biomedical Informatics 3890 </div> 3891 3892 <div class="publinks"> 3893 3894 3895 3896 3897 3898 <a href="https://www.sciencedirect.com/science/article/pii/S1532046423000278"><i class="fas fa-external-link-alt"></i> sciencedirect.com </a> 3899 3900 3901 3902 3903 3904 3905 3906 3907 | 3908 3909 <a href="/assets/papers/Tan et al. - 2023 - Informative missingness What can we learn from pa.pdf">pdf</a> 3910 3911 3912 </div> 3913</div> 3914 3915<div class="pubitem"> 3916 <div class="pubtitle" id="rodriguesSLUGFeatureSelection2022"> 3917 SLUG: Feature Selection Using Genetic Algorithms and Genetic Programming 3918 </div> 3919 <div class="pubauthors"> 3920 3921 3922 3923 3924 3925 3926 Nuno M. Rodrigues, 3927 3928 3929 3930 João E. Batista, 3931 3932 3933 3934 William La Cava, 3935 3936 3937 3938 Leonardo Vanneschi, 3939 3940 3941 3942 Sara Silva 3943 3944 (2022) 3945 </div> 3946 3947 3948 3949 3950 3951 <div class="pubjournal"> 3952 European Conference on Genetic Programming (EuroGP) 3953 </div> 3954 3955 <div class="publinks"> 3956 3957 3958 3959 3960 3961 <a href="https://link.springer.com/10.1007/978-3-031-02056-8_5"><i class="fas fa-external-link-alt"></i> link.springer.com </a> 3962 3963 3964 3965 3966 3967 3968 3969 3970 | 3971 3972 <a href="/assets/papers/Rodrigues et al. - 2022 - SLUG Feature Selection Using Genetic Algorithms a.pdf">pdf</a> 3973 3974 3975 </div> 3976</div> 3977 3978<div class="pubitem"> 3979 <div class="pubtitle" id="orzechowskiComparativeStudyGPbased2022"> 3980 A comparative study of GP-based and state-of-the-art classifiers on a
3980synthetic machine learning benchmark 3981 </div> 3982 <div class="pubauthors"> 3983 3984 3985 3986 3987 3988 3989 Patryk Orzechowski, 3990 3991 3992 3993 PaweÅ Renc, 3994 3995 3996 3997 William La Cava, 3998 3999 4000 4001 Jason H. Moore, 4002 4003 4004 4005 Arkadiusz Sitek, 4006 4007 4008 4009 Jaroslaw WÄ s, 4010 4011 4012 4013 Joost Wagenaar 4014 4015 (2022) 4016 </div> 4017 4018 4019 4020 4021 4022 <div class="pubjournal"> 4023 GECCO '22: Genetic and Evolutionary Computation Conference 4024 </div> 4025 4026 <div class="publinks"> 4027 4028 4029 4030 4031 4032 <a href="https://dl.acm.org/doi/10.1145/3520304.3529056"><i class="fas fa-external-link-alt"></i> dl.acm.org </a> 4033 4034 4035 4036 4037 4038 4039 4040 4041 | 4042 4043 <a href="/assets/papers/Orzechowski et al. - 2022 - A comparative study of GP-based and state-of-the-a.pdf">pdf</a> 4044 4045 4046 </div> 4047</div> 4048 4049<div class="pubitem"> 4050 <div class="pubtitle" id="helmuthPopulationDiversityLeads2022"> 4051 Population Diversity Leads to Short Running Times of Lexicase Selection 4052 </div> 4053 <div class="pubauthors"> 4054 4055 4056 4057 4058 4059 4060 Thomas Helmuth, 4061 4062 4063 4064 Johannes Lengler, 4065 4066 4067 4068 William La Cava 4069 4070 (2022) 4071 </div> 4072 4073 4074 4075 4076 4077 <div class="pubjournal"> 4078 Parallel Problem Solving from Nature 4079 </div> 4080 4081 <div class="publinks"> 4082 4083 4084 4085 4086 4087 <a href="https://link.springer.com/chapter/10.1007/978-3-031-14721-0_34"><i class="fas fa-external-link-alt"></i> link.springer.com </a> 4088 4089 4090 4091 | 4092 <a href="http://arxiv.org/abs/2204.06461">arXiv</a> 4093 4094 4095 4096 4097 4098 4099 | 4100 4101 <a href="/assets/papers/Helmuth et al. - 2022 - Population Diversity Leads to Short Running Times.pdf">pdf</a> 4102 4103 4104 4105 4106 4107 4108 4109 4110 | 4111 <a href="https://cavalab.github.io/2022/08/23/lexicase-running-time.html">blog</a> 4112 4113 4114 4115 </div> 4116</div> 4117 4118<div class="pubitem"> 4119 <div class="pubtitle" id="romanoPMLBV10Opensource2022"> 4120 PMLB v1.0: an open-source dataset collection for benchmarking machine learning methods 4121 </div> 4122 <div class="pubauthors"> 4123 4124 4125 4126 4127 4128 4129 Joseph D Romano, 4130 4131 4132 4133 Trang T Le, 4134 4135 4136 4137 William La Cava, 4138 4139 4140 4141 John T Gregg, 4142 4143 4144 4145 Daniel J Goldberg, 4146 4147 4148 4149 Praneel Chakraborty, 4150 4151 4152 4153 Natasha L Ray, 4154 4155 4156 4157 Daniel Himmelstein, 4158 4159 4160 4161 Weixuan Fu, 4162 4163 4164 4165 Jason H Moore 4166 4167 (2022) 4168 </div> 4169 4170 4171 4172 4173 4174 <div class="pubjournal"> 4175 Bioinformatics 4176 </div> 4177 4178 <div class="publinks"> 4179 4180 4181 4182 4183 4184 <a href="https://academic.oup.com/bioinformatics/article/38/3/878/6408434"><i class="fas fa-external-link-alt"></i> academic.oup.com </a> 4185 4186 4187 4188 | 4189 <a href="https://arxiv.org/abs/2012.00058">arXiv</a> 4190 4191 4192 4193 4194 4195 4196 | 4197 4198 <a href="/assets/papers/Romano et al. - 2022 - PMLB v1.0 an open-source dataset collection for b.pdf">pdf</a> 4199 4200 4201 </div> 4202</div> 4203 4204<div class="pubitem"> 4205 <div class="pubtitle" id="lacavaContemporarySymbolicRegression2021a">
4206 Contemporary Symbolic Regression Methods and their Relative Performance 4207 </div> 4208 <div class="pubauthors"> 4209 4210 4211 4212 4213 4214 4215 William La Cava, 4216 4217 4218 4219 Patryk Orzechowski, 4220 4221 4222 4223 Bogdan Burlacu, 4224 4225 4226 4227 Fabricio de Franca, 4228 4229 4230 4231 Marco Virgolin, 4232 4233 4234 4235 Ying Jin, 4236 4237 4238 4239 Michael Kommenda, 4240 4241 4242 4243 Jason Moore 4244 4245 (2021) 4246 </div> 4247 4248 4249 4250 4251 4252 <div class="pubjournal"> 4253 Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks (NeurIPS) 4254 </div> 4255 4256 <div class="publinks"> 4257 4258 4259 4260 4261 4262 <a href="https://datasets-benchmarks-proceedings.neurips.cc/paper/2021/hash/c0c7c76d30bd3dcaefc96f40275bdc0a-Abstract-round1.html"><i class="fas fa-external-link-alt"></i> datasets-benchmarks-proceedings.neurips.cc </a> 4263 4264 4265 4266 | 4267 <a href="https://arxiv.org/abs/2107.14351">arXiv</a> 4268 4269 4270 4271 4272 4273 4274 | 4275 4276 <a href="/assets/papers/La Cava et al. - 2021 - Contemporary Symbolic Regression Methods and their.pdf">pdf</a> 4277 4278 4279 4280 4281 4282 4283 4284 4285 | 4286 <a href="https://cavalab.org/srbench">
4286code</a> 4287 4288 4289 4290 </div> 4291</div> 4292 4293<div class="pubitem"> 4294 <div class="pubtitle" id="helmuthLexicaseSelection2021"> 4295 Lexicase Selection 4296 </div> 4297 <div class="pubauthors"> 4298 4299 4300 4301 4302 4303 4304 Thomas Helmuth and 4305 4306 4307 4308 William La Cava 4309 4310 (2021) 4311 </div> 4312 4313 4314 4315 4316 4317 <div class="pubjournal"> 4318 Proceedings of the Genetic and Evolutionary Computation Conference Companion 4319 </div> 4320 4321 <div class="publinks"> 4322 4323 4324 4325 4326 4327 <a href="https://doi.org/10.1145/3449726.3461408"><i class="fas fa-external-link-alt"></i> doi.org </a> 4328 4329 4330 4331 4332 4333 4334 4335 4336 | 4337 4338 <a href="/assets/papers/Helmuth and La Cava - 2021 - Lexicase Selection.pdf">pdf</a> 4339 4340 4341 </div> 4342</div> 4343 4344<div class="pubitem"> 4345 <div class="pubtitle" id="danaiControllerDesignSymbolic2021"> 4346 Controller design by symbolic regression 4347 </div> 4348 <div class="pubauthors"> 4349 4350 4351 4352 4353 4354 4355 Kourosh Danai and 4356 4357 4358 4359 William G. La Cava 4360 4361 (2021) 4362 </div> 4363 4364 4365 4366 4367 4368 <div class="pubjournal"> 4369 Mechanical Systems and Signal Processing 4370 </div> 4371 4372 <div class="publinks"> 4373 4374 4375 4376 4377 4378 <a href="http://www.sciencedirect.com/science/article/pii/S0888327020307342"><i class="fas fa-external-link-alt"></i> sciencedirect.com </a> 4379 4380 4381 4382 4383 4384 4385 4386 4387 | 4388 4389 <a href="/assets/papers/Danai and La Cava - 2021 - Controller design by symbolic regression.pdf">pdf</a> 4390 4391 4392 </div> 4393</div> 4394 4395<div class="pubitem"> 4396 <div class="pubtitle" id="lacavaGeneticProgrammingApproaches2020a"> 4397 Genetic programming approaches to learning fair classifiers 4398 </div> 4399 <div class="pubauthors"> 4400 4401 4402 4403 4404 4405 4406 William La Cava and 4407 4408 4409 4410 Jason H. Moore 4411 4412 (2020) 4413 </div> 4414 4415 4416 4417 4418 4419 <div class="pubjournal"> 4420 GECCO '20 4421 </div> 4422 4423 <div class="publinks"> 4424 4425 4426 4427 4428 4429 <a href="https://dl.acm.org/doi/abs/10.1145/3377930.3390157"><i class="fas fa-external-link-alt"></i> dl.acm.org </a> 4430 4431 4432 4433 | 4434 <a href="https://arxiv.org/abs/2004.13282">arXiv</a> 4435 4436 4437 4438 4439 4440 4441 | 4442 4443 <a href="/assets/papers/La Cava and Moore - 2020 - Genetic programming approaches to learning fair cl.pdf">pdf</a> 4444 4445 4446 4447 4448 4449 4450 4451 4452 | 4453 <i class="fas fa-trophy"></i> 4454 Best Paper Award 4455 4456 4457 4458 </div> 4459</div> 4460 4461<div class="pubitem"> 4462 <div class="pubtitle" id="bartz-beielsteinBenchmarkingOptimizationBest2020"> 4463 Benchmarking in Optimization: Best Practice and Open Issues 4464 </div> 4465 <div class="pubauthors"> 4466 4467 4468 4469 4470 4471 4472 Thomas Bartz-Beielstein, 4473 4474 4475 4476 Carola Doerr, 4477 4478 4479 4480 Daan Berg, 4481 4482 4483 4484 Jakob Bossek, 4485 4486 4487 4488 Sowmya Chandrasekaran, 4489 4490 4491 4492 Tome Eftimov, 4493 4494 4495 4496 Andreas Fischbach, 4497 4498 4499 4500 Pascal Kerschke, 4501 4502 4503 4504 William La Cava, 4505 4506 4507 4508 Manuel Lopez-Ibanez, 4509 4510 4511 4512 Katherine M. Malan, 4513 4514 4515 4516 Jason H. Moore, 4517 4518 4519
4520 Boris Naujoks, 4521 4522 4523 4524 Patryk Orzechowski, 4525 4526 4527 4528 Vanessa Volz, 4529 4530 4531 4532 Markus Wagner, 4533 4534 4535 4536 Thomas Weise 4537 4538 (2020) 4539 </div> 4540 4541 4542 4543 4544 4545 <div class="pubinfo"> 4546 Preprint 4547 </div> 4548 4549 <div class="publinks"> 4550 4551 4552 4553 4554 4555 <a href="http://arxiv.org/abs/2007.03488"><i class="fas fa-external-link-alt"></i> arxiv.org </a> 4556 4557 4558 4559 4560 4561 4562 4563 4564 | 4565 4566 <a href="/assets/papers/Bartz-Beielstein et al. - 2020 - Benchmarking in Optimization Best Practice and Op.pdf">pdf</a> 4567 4568 4569 </div> 4570</div> 4571 4572<div class="pubitem"> 4573 <div class="pubtitle" id="lacavaEvaluatingRecommenderSystems2020"> 4574 Evaluating recommender systems for AI-driven biomedical informatics 4575 </div> 4576 <div class="pubauthors"> 4577 4578 4579 4580 4581 4582 4583 William La Cava, 4584 4585 4586 4587 Heather Williams, 4588 4589 4590 4591 Weixuan Fu, 4592 4593 4594 4595 Steve Vitale, 4596 4597 4598 4599 Durga Srivatsan, 4600 4601 4602 4603 Jason H Moore 4604 4605 (2020) 4606 </div> 4607 4608 4609 4610 4611 4612 <div class="pubjournal"> 4613 Bioinformatics 4614 </div> 4615 4616 <div class="publinks"> 4617 4618 4619 4620 4621 4622 <a href="https://doi.org/10.1093/bioinformatics/btaa698"><i class="fas fa-external-link-alt"></i> doi.org </a> 4623 4624 4625 4626 | 4627 <a href="1905.09205">arXiv</a> 4628 4629 4630 4631 4632 4633 4634 | 4635 4636 <a href="/assets/papers/La Cava et al. - 2020 - Evaluating recommender systems for AI-driven biome.pdf">pdf</a> 4637 4638 4639 </div> 4640</div> 4641 4642<div class="pubitem">
4643 <div class="pubtitle" id="lacavaLearningFeatureSpaces2020"> 4644 Learning feature spaces for regression with genetic programming 4645 </div> 4646 <div class="pubauthors"> 4647 4648 4649 4650 4651 4652 4653 William La Cava and 4654 4655 4656 4657 Jason H. Moore 4658 4659 (2020) 4660 </div> 4661 4662 4663 4664 4665 4666 <div class="pubjournal"> 4667 Genetic Programming and Evolvable Machines 4668 </div> 4669 4670 <div class="publinks"> 4671 4672 4673 4674 4675 4676 <a href="https://link.springer.com/article/10.1007/s10710-020-09383-4"><i class="fas fa-external-link-alt"></i> link.springer.com </a> 4677 4678 4679 4680 4681 4682 4683 4684 4685 | 4686 4687 <a href="/assets/papers/La Cava and Moore - 2020 - Learning feature spaces for regression with geneti.pdf">pdf</a> 4688 4689 4690 </div> 4691</div> 4692 4693<div class="pubitem"> 4694 <div class="pubtitle" id="lacavaInterpretationMachineLearning2019"> 4695 Interpretation of machine learning predictions for patient outcomes in electronic health records 4696 </div> 4697 <div class="pubauthors"> 4698 4699 4700 4701 4702 4703 4704 William La Cava, 4705 4706 4707 4708 Christopher R. Bauer, 4709 4710 4711 4712 Jason H. Moore, 4713 4714 4715 4716 Sarah A. Pendergrass 4717 4718 (2019) 4719 </div> 4720 4721 4722 4723 4724 4725 <div class="pubjournal"> 4726 AMIA Annual Symposium 4727 </div> 4728 4729 <div class="publinks"> 4730 4731 4732 4733 4734 4735 <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7153071/"><i class="fas fa-external-link-alt"></i> ncbi.nlm.nih.gov </a> 4736 4737 4738 4739 | 4740 <a href="https://arxiv.org/abs/1903.12074">arXiv</a> 4741 4742 4743 4744 4745 4746 4747 | 4748 4749 <a href="/assets/papers/La Cava et al. - 2019 - Interpretation of machine learning predictions for.pdf">pdf</a> 4750 4751 4752 4753 4754 4755 4756 4757 4758 4759 4760 4761 </div> 4762</div> 4763 4764<div class="pubitem"> 4765 <div class="pubtitle" id="lacavaLearningConciseRepresentations2019a"> 4766 Learning concise representations for regression by evolving networks of trees 4767 </div> 4768 <div class="pubauthors"> 4769 4770 4771 4772 4773 4774 4775 William La Cava, 4776 4777 4778 4779 Tilak Raj Singh, 4780 4781 4782 4783 James Taggart, 4784 4785 4786 4787 Srinivas Suri, 4788 4789 4790 4791 Jason H. Moore 4792 4793 (2019) 4794 </div> 4795 4796 4797 4798 4799 4800 <div class="pubjournal"> 4801 International Conference on Learning Representations (ICLR) 4802 </div> 4803 4804 <div class="publinks"> 4805 4806 4807 4808 4809 4810 <a href="https://arxiv.org/abs/1807.00981"><i class="fas fa-external-link-alt"></i> arxiv.org </a> 4811 4812 4813 4814 | 4815 <a href="1807.00981">arxiv.org</a> 4816 4817 4818 4819 4820 4821 4822 | 4823 4824 <a href="/assets/papers/La Cava et al. - 2019 - Learning concise representations for regression by.pdf">pdf</a> 4825 4826 4827 </div> 4828</div> 4829 4830<div class="pubitem"> 4831 <div class="pubtitle" id="lacavaProbabilisticMultiobjectiveAnalysis2019"> 4832 A probabilistic and multi-objective analysis of lexicase selection and epsilon-lexicase selection 4833 </div> 4834 <div class="pubauthors"> 4835 4836 4837 4838 4839 4840 4841 William La Cava, 4842 4843 4844 4845 Thomas Helmuth, 4846 4847 4848 4849 Lee Spector, 4850 4851 4852 4853 Jason H. Moore 4854 4855 (2019) 4856 </div> 4857 4858 4859 4860 4861 4862 <div class="pubjournal"> 4863 Evolutionary Computation 4864 </div> 4865 4866 <div class="publinks"> 4867 4868 4869 4870 4871 4872 <a href="https://direct.mit.edu/evco/article-abstract/27/3/377/94969/A-Probabilistic-and-Multi-Objective-Analysis-of"><i class="fas fa-external-link-alt"></i> direct.mit.edu </a> 4873 4874 4875 4876 | 4877 <a href="https://arxiv.org/abs/1709.05394">arXiv</a> 4878 4879 4880 4881 4882 4883 4884 | 4885 4886 <a href="/assets/papers/La Cava et al. - 2019 - A probabilistic and multi-objective analysis of le.pdf">pdf</a> 4887 4888 4889 </div> 4890</div> 4891 4892<div class="pubitem"> 4893 <div class="pubtitle" id="lacavaSemanticVariationOperators2019"> 4894 Semantic variation operators for multidimensional genetic programming 4895 </div> 4896 <div class="pubauthors"> 4897 4898 4899 4900 4901 4902 4903 William La Cava and 4904 4905 4906 4907 Jason H. Moore 4908 4909 (2019) 4910 </div> 4911 4912 4913 4914 4915 4916 <div class="pubjournal"> 4917 GECCO '19 4918 </div> 4919 4920 <div class="publinks"> 4921 4922 4923 4924 4925 4926 <a href="https://doi.org/10.1145/3321707.3321776"><i class="fas fa-external-link-alt"></i> doi.org </a> 4927 4928 4929 4930 | 4931 <a href="http://arxiv.org/abs/1904.08577">arXiv</a> 4932 4933 4934 4935 4936 4937 4938 | 4939 4940 <a href="/assets/papers/La Cava and Moore - 2019 - Semantic variation operators for multidimensional.pdf">pdf</a> 4941 4942 4943 </div> 4944</div> 4945 4946<div class="pubitem"> 4947 <div class="pubtitle" id="spectorRelaxationsLexicaseParent2018"> 4948 Relaxations of lexicase parent selection 4949 </div> 4950 <div class="pubauthors"> 4951 4952 4953 4954 4955 4956 4957 Lee Spector, 4958 4959 4960 4961 William La Cava, 4962 4963 4964 4965 Saul Shanabrook, 4966 4967 4968 4969 Thomas Helmuth, 4970 4971 4972 4973 Edward Pantridge 4974 4975 (2018) 4976 </div> 4977 4978 4979 4980 4981 4982 <div class="pubjournal"> 4983 Genetic Programming Theory and Practice XV 4984 </div> 4985 4986 <div class="publinks"> 4987 4988 4989 4990 4991 4992 <a href="https://link.springer.com/chapter/10.1007/978-3-319-90512-9_7"><i class="fas fa-external-link-alt"></i> link.springer.com </a> 4993 4994 4995 4996 4997 4998 4999 5000 5001 | 5002 5003 <a href="/assets/papers/Spector et al. - 2018 - Relaxations of lexicase parent selection.pdf">pdf</a> 5004 5005 5006 </div> 5007</div> 5008 5009<div class="pubitem"> 5010 <div class="pubtitle" id="urbanowiczReliefbasedFeatureSelection2018"> 5011 Relief-based feature selection: Introduction and review 5012 </div> 5013 <div class="pubauthors"> 5014 5015 5016 5017 5018 5019 5020 Ryan J. Urbanowicz, 5021 5022 5023 5024 Melissa Meeker, 5025 5026 5027 5028 William La Cava, 5029 5030 5031 5032 Randal S. Olson, 5033 5034 5035 5036 Jason H. Moore 5037 5038 (2018) 5039 </div> 5040 5041 5042 5043 5044 5045 <div class="pubjournal">
5046 Journal of Biomedical Informatics 5047 </div> 5048 5049 <div class="publinks"> 5050 5051 5052 5053 5054 5055 <a href="https://www.sciencedirect.com/science/article/pii/S1532046418301400"><i class="fas fa-external-link-alt"></i> sciencedirect.com </a> 5056 5057 5058 5059 5060 5061 5062 5063 5064 | 5065 5066 <a href="/assets/papers/Urbanowicz et al. - 2018 - Relief-based feature selection Introduction and r.pdf">pdf</a> 5067 5068 5069 </div> 5070</div> 5071 5072<div class="pubitem"> 5073 <div class="pubtitle" id="lacavaAnalysislexicaseSelection2018"> 5074 An analysis of ϵ-lexicase selection for large-scale many-objective optimization 5075 </div> 5076 <div class="pubauthors"> 5077 5078 5079 5080 5081 5082 5083 William La Cava and 5084 5085 5086 5087 Jason H. Moore 5088 5089 (2018) 5090 </div> 5091 5092 5093 5094 5095 5096 <div class="pubjournal"> 5097 GECCO '18: Genetic and Evolutionary Computation Conference 5098 </div> 5099 5100 <div class="publinks"> 5101 5102 5103 5104 5105 5106 <a href="https://dl.acm.org/doi/10.1145/3205651.3205656"><i class="fas fa-external-link-alt"></i> dl.acm.org </a> 5107 5108 5109 5110 5111 5112 5113 5114 5115 | 5116 5117 <a href="/assets/papers/La Cava and Moore - 2018 - An analysis of ϵ-lexicase selection for large-scal.pdf">pdf</a> 5118 5119 5120 </div> 5121</div> 5122 5123<div class="pubitem"> 5124 <div class="pubtitle" id="lacavaBehavioralSearchDrivers2018"> 5125 Behavioral search drivers and the role of elitism in soft robotics 5126 </div> 5127 <div class="pubauthors"> 5128 5129 5130 5131 5132 5133 5134 William La Cava and 5135 5136 5137 5138 Jason H. Moore 5139 5140 (2018) 5141 </div> 5142 5143 5144 5145 5146 5147 <div class="pubjournal"> 5148 Artificial Life 5149 </div> 5150 5151 <div class="publinks"> 5152 5153 5154 5155 5156 5157 <a href="https://www.mitpressjournals.org/doi/abs/10.1162/isal_a_00044"><i class="fas fa-external-link-alt"></i> mitpressjournals.org </a> 5158 5159 5160 5161 5162 5163 5164 5165 5166 | 5167 5168 <a href="/assets/papers/La Cava and Moore - 2018 - Behavioral search drivers and the role of elitism.pdf">pdf</a> 5169 5170 5171 </div> 5172</div> 5173 5174<div class="pubitem"> 5175 <div class="pubtitle" id="lacavaMultidimensionalGeneticProgramming2018"> 5176 Multidimensional genetic programming for multiclass classification 5177 </div> 5178 <div class="pubauthors"> 5179 5180 5181 5182 5183 5184 5185 William La Cava, 5186 5187 5188 5189 Sara Silva, 5190 5191 5192 5193 Kourosh Danai, 5194 5195 5196 5197 Lee Spector, 5198 5199 5200 5201 Leonardo Vanneschi, 5202 5203 5204 5205 Jason H. Moore 5206 5207 (2018) 5208 </div> 5209 5210 5211 5212 5213 5214 <div class="pubjournal"> 5215 Swarm and Evolutionary Computation 5216 </div> 5217 5218 <div class="publinks"> 5219 5220 5221 5222 5223 5224 <a href="http://www.sciencedirect.com/science/article/pii/S2210650217309136"><i class="fas fa-external-link-alt"></i> sciencedirect.com </a> 5225 5226 5227 5228 5229 5230 5231 5232 5233 | 5234 5235 <a href="/assets/papers/La Cava et al. - 2018 - Multidimensional genetic programming for multiclas.pdf">pdf</a> 5236 5237 5238 </div> 5239</div> 5240 5241<div class="pubitem"> 5242 <div class="pubtitle" id="orzechowskiWhereAreWe2018b"> 5243 Where are we now? A large benchmark study of recent symbolic regression methods 5244 </div> 5245 <div class="pubauthors"> 5246 5247 5248 5249 5250 5251 5252 Patryk Orzechowski, 5253 5254 5255 5256 William La Cava, 5257 5258 5259 5260 Jason H. Moore 5261 5262 (2018) 5263 </div> 5264 5265 5266 5267 5268 5269 <div class="pubjournal"> 5270 GECCO '18 5271 </div> 5272 5273 <div class="publinks"> 5274 5275 5276 5277 5278 5279 <a href="https://dl.acm.org/doi/10.1145/3205455.3205539"><i class="fas fa-external-link-alt"></i> dl.acm.org </a> 5280 5281 5282 5283 | 5284 <a href="http://arxiv.org/abs/1804.09331">arXiv</a> 5285 5286 5287 5288 5289 5290 5291 | 5292 5293 <a href="/assets/papers/Orzechowski et al. - 2018 - Where are we now A large benchmark study of recen.pdf">pdf</a> 5294 5295 5296 </div> 5297</div> 5298 5299<div class="pubitem"> 5300 <div class="pubtitle" id="lacavaEnsembleRepresentationLearning2017"> 5301 Ensemble representation learning: an analysis of fitness and survival for wrapper-based genetic programming methods 5302 </div> 5303 <div class="pubauthors"> 5304 5305 5306 5307 5308 5309 5310 William La Cava and 5311 5312 5313 5314 Jason H Moore 5315 5316 (2017) 5317 </div> 5318 5319 5320 5321 5322 5323 <div class="pubjournal"> 5324 GECCO '17 5325 </div> 5326 5327 <div class="publinks"> 5328 5329 5330 5331 5332 5333 <a href="https://dl.acm.org/doi/10.1145/3071178.3071215"><i class="fas fa-external-link-alt"></i> dl.acm.org </a> 5334 5335 5336 5337 | 5338 <a href="https://arxiv.org/abs/1703.06934">arXiv</a> 5339 5340 5341 5342 5343 5344 5345 | 5346 5347 <a href="/assets/papers/La Cava and Moore - 2017 - Ensemble representation learning an analysis of f.pdf">pdf</a> 5348 5349 5350 </div> 5351</div> 5352 5353<div class="pubitem"> 5354 <div class="pubtitle" id="olsonPMLBLargeBenchmark2017"> 5355 PMLB: A Large Benchmark Suite for Machine Learning Evaluation and Comparison 5356 </div> 5357 <div class="pubauthors"> 5358 5359 5360 5361 5362 5363 5364 Randal S. Olson, 5365 5366 5367 5368 William La Cava, 5369 5370 5371 5372 Patryk Orzechowski, 5373 5374 5375 5376 Ryan J. Urbanowicz, 5377 5378 5379 5380 Jason H. Moore 5381 5382 (2017) 5383 </div> 5384 5385 5386 5387 5388 5389 <div class="pubjournal"> 5390 BioData Mining 5391 </div> 5392 5393 <div class="publinks"> 5394 5395 5396 5397 5398 5399 <a href="https://biodatamining.biomedcentral.com/articles/10.1186/s13040-017-0154-4"><i class="fas fa-external-link-alt"></i> biodatamining.biomedcentral.com </a> 5400 5401 5402 5403 | 5404 <a href="https://arxiv.org/abs/1703.00512">arXiv</a> 5405 5406 5407 5408 5409 5410 5411 | 5412 5413 <a href="/assets/papers/Olson et al. - 2017 - PMLB A Large Benchmark Suite for Machine Learning.pdf">pdf</a> 5414 5415 5416 5417 5418 5419 5420 5421 5422 5423 5424 5425 </div> 5426</div> 5427 5428<div class="pubitem"> 5429 <div class="pubtitle" id="olsonSystemAccessibleArtificial2017"> 5430 A System for Accessible Artificial Intelligence 5431 </div> 5432 <div class="pubauthors"> 5433 5434 5435 5436 5437 5438 5439 Randal S Olson, 5440 5441 5442 5443 Moshe Sipper, 5444 5445 5446 5447 William La Cava, 5448 5449 5450 5451 Sharon Tartarone, 5452 5453 5454 5455 Steven Vitale, 5456 5457 5458 5459 Weixuan Fu, 5460 5461 5462 5463 John H Holmes, 5464 5465 5466 5467 Jason H. Moore 5468 5469 (2017) 5470 </div> 5471 5472 5473 5474 5475 5476 <div class="pubjournal"> 5477 Genetic Programming Theory and Practice XIV 5478 </div> 5479 5480 <div class="publinks"> 5481 5482 5483 5484 5485 5486 <a href="https://link.springer.com/chapter/10.1007/978-3-319-90512-9_8"><i class="fas fa-external-link-alt"></i> link.springer.com </a> 5487 5488 5489 5490 | 5491 <a href="https://arxiv.org/abs/1705.00594">arXiv</a> 5492 5493 5494 5495 5496 5497 5498 | 5499 5500 <a href="/assets/papers/Olson et al. - 2017 - A System for Accessible Artificial Intelligence.pdf">pdf</a> 5501 5502 5503 </div> 5504</div> 5505 5506<div class="pubitem"> 5507 <div class="pubtitle" id="olsonDatadrivenAdviceApplying2017"> 5508 Data-driven Advice for Applying Machine Learning to Bioinformatics Problems 5509 </div> 5510 <div class="pubauthors"> 5511 5512 5513 5514 5515 5516 5517 Randal S. Olson, 5518 5519 5520 5521 William La Cava, 5522 5523 5524 5525 Zairah Mustahsan, 5526 5527 5528 5529 Akshay Varik, 5530 5531 5532 5533 Jason H. Moore 5534 5535 (2017) 5536 </div> 5537 5538 5539 5540 5541 5542 <div class="pubjournal"> 5543 Pacific Symposium on Biocomputing (PSB) 5544 </div> 5545 5546 <div class="publinks"> 5547 5548 5549 5550 5551 5552 <a href="https://psb.stanford.edu/psb-online/proceedings/psb18/ols
5552on.pdf"><i class="fas fa-external-link-alt"></i> psb.stanford.edu </a> 5553 5554 5555 5556 | 5557 <a href="http://arxiv.org/abs/1708.05070">arXiv</a> 5558 5559 5560 5561 5562 5563 5564 | 5565 5566 <a href="/assets/papers/Olson et al. - 2017 - Data-driven Advice for Applying Machine Learning t.pdf">pdf</a> 5567 5568 5569 5570 5571 5572 5573 5574 5575 5576 5577 5578 </div> 5579</div> 5580 5581<div class="pubitem"> 5582 <div class="pubtitle" id="lacavaRestructuringControllersAccommodate2017"> 5583 Restructuring Controllers to Accommodate Plant Nonlinearities 5584 </div> 5585 <div class="pubauthors"> 5586 5587 5588 5589 5590 5591 5592 William G. La Cava, 5593 5594 5595 5596 Kushal Sahare, 5597 5598 5599 5600 Kourosh Danai 5601 5602 (2017) 5603 </div> 5604 5605 5606 5607 5608 5609 <div class="pubjournal"> 5610 Journal of Dynamic Systems, Measurement, and Control 5611 </div> 5612 5613 <div class="publinks"> 5614 5615 5616 5617 5618 5619 <a href="https://asmedigitalcollection.asme.org/dynamicsystems/article/doi/10.1115/1.4035870/384813/Restructuring-Controllers-to-Accommodate-Plant"><i class="fas fa-external-link-alt"></i> asmedigitalcollection.asme.org </a> 5620 5621 5622 5623 5624 5625 5626 5627 5628 | 5629 5630 <a href="/assets/papers/La Cava et al. - 2017 - Restructuring Controllers to A
5630ccommodate Plant Non.pdf">pdf</a> 5631 5632 5633 </div> 5634</div> 5635 5636<div class="pubitem"> 5637 <div class="pubtitle" id="lacavaGeneralFeatureEngineering2017"> 5638 A General Feature Engineering Wrapper for Machine Learning Using \epsilon -Lexicase Survival 5639 </div> 5640 <div class="pubauthors"> 5641 5642 5643 5644 5645 5646 5647 William La Cava and 5648 5649 5650 5651 Jason Moore 5652 5653 (2017) 5654 </div> 5655 5656 5657 5658 5659 5660 <div class="pubjournal"> 5661 European Conference on Genetic Programming 5662 </div> 5663 5664 <div class="publinks"> 5665 5666 5667 5668 5669 5670 <a href="https://link.springer.com/chapter/10.1007/978-3-319-55696-3_6"><i class="fas fa-external-link-alt"></i> link.springer.com </a> 5671 5672 5673 5674 5675 5676 5677 5678 5679 | 5680 5681 <a href="/assets/papers/La Cava and Moore - 2017 - A General Feature Engineering Wrapper for Machine.pdf">pdf</a> 5682 5683 5684 </div> 5685</div> 5686 5687<div class="pubitem"> 5688 <div class="pubtitle" id="lacavaGeneticProgrammingRepresentations2017"> 5689 Genetic Programming Representations for Multi-dimensional Feature Learning in Biomedical Classification 5690 </div> 5691 <div class="pubauthors"> 5692 5693 5694 5695 5696 5697 5698 William La Cava, 5699 5700 5701 5702 Sara Silva, 5703 5704 5705 5706 Leonardo Vanneschi, 5707 5708 5709 5710 Lee Spector, 5711 5712 5713 5714 Jason Moore 5715 5716 (2017) 5717 </div> 5718 5719 5720 5721 5722 5723 <div class="pubjournal"> 5724 European Conference on the Applications of Evolutionary Computation 5725 </div> 5726 5727 <div class="publinks"> 5728 5729 5730 5731 5732 5733 <a href="https://link.springer.com/chapter/10.1007/978-3-319-55849-3_11"><i class="fas fa-external-link-alt"></i> link.springer.com </a> 5734 5735 5736 5737 5738 5739 5740 5741 5742 | 5743 5744 <a href="/assets/papers/La Cava et al. - 2017 - Genetic Programming Representations for Multi-dime.pdf">pdf</a> 5745 5746 5747 </div> 5748</div> 5749 5750<div class="pubitem"> 5751 <div class="pubtitle" id="lacavaAutomaticDevelopmentAdaptation2016"> 5752 Automatic Development and Adaptation of Concise Nonlinear Models for System Identification 5753 </div> 5754 <div class="pubauthors"> 5755 5756 5757 5758 5759 5760 5761 William G. La Cava 5762 5763 (2016) 5764 </div> 5765 5766 5767 5768 5769 5770 <div class="pubjournal"> 5771 Thesis 5772 </div> 5773 5774 <div class="publinks"> 5775 5776 5777 5778 5779 5780 <a href="http://scholarworks.umass.edu/dissertations_2/731/"><i class="fas fa-external-link-alt"></i> scholarworks.umass.edu </a> 5781 5782 5783 5784 5785 5786 5787 5788 5789 | 5790 5791 <a href="/assets/papers/La Cava - 2016 - Automatic Development and Adaptation of Concise No.pdf">pdf</a> 5792 5793 5794 </div> 5795</div> 5796 5797<div class="pubitem"> 5798 <div class="pubtitle" id="lacavaEpsilonLexicaseSelectionRegression2016"> 5799 Epsilon-Lexicase Selection for Regression 5800 </div> 5801 <div class="pubauthors"> 5802 5803 5804 5805 5806 5807 5808 William La Cava, 5809 5810 5811 5812 Lee Spector, 5813 5814 5815 5816 Kourosh Danai 5817 5818 (2016) 5819 </div> 5820 5821 5822 5823 5824 5825 <div class="pubjournal"> 5826 Proceedings of the Genetic and Evolutionary Computation Conference 2016 5827 </div> 5828 5829 <div class="publinks"> 5830 5831 5832 5833 5834 5835 <a href="http://doi.acm.org/10.1145/2908812.2908898"><i class="fas fa-external-link-alt"></i> doi.acm.org </a> 5836 5837 5838 5839 5840 5841 5842 5843 5844 | 5845 5846 <a href="/assets/papers/La Cava et al. - 2016 - Epsilon-Lexicase Selection for Regression.pdf">pdf</a> 5847 5848 5849 </div> 5850</div> 5851 5852<div class="pubitem"> 5853 <div class="pubtitle" id="lacavaInferenceCompactNonlinear2016"> 5854 Inference of compact nonlinear dynamic models by epigenetic local search 5855 </div> 5856 <div class="pubauthors"> 5857 5858 5859 5860 5861 5862 5863 William La Cava, 5864 5865 5866 5867 Kourosh Danai, 5868 5869 5870 5871 Lee Spector 5872 5873 (2016) 5874 </div> 5875 5876 5877 5878 5879 5880 <div class="pubjournal"> 5881 Engineering Applications of Artificial Intelligence 5882 </div> 5883 5884 <div class="publinks"> 5885 5886 5887 5888 5889 5890 <a href="http://www.sciencedirect.com/science/article/pii/S0952197616301294"><i class="fas fa-external-link-alt"></i> sciencedirect.com </a> 5891 5892 5893 5894 5895 5896 5897 5898 5899 | 5900 5901 <a href="/assets/papers/La Cava et al. - 2016 - Inference of compact nonlinear dynamic models by e.pdf">pdf</a> 5902 5903 5904 </div> 5905</div> 5906 5907<div class="pubitem"> 5908 <div class="pubtitle" id="lacavaAutomaticIdentificationWind2016"> 5909 Automatic identification of wind turbine models using evolutionary multiobjective optimization 5910 </div> 5911 <div class="pubauthors"> 5912 5913 5914 5915 5916 5917 5918 William La Cava, 5919 5920 5921 5922 Kourosh Danai, 5923 5924 5925 5926 Lee Spector, 5927 5928 5929 5930 Paul Fleming, 5931 5932 5933 5934 Alan Wright, 5935 5936 5937 5938 Matthew Lackner 5939 5940 (2016) 5941 </div> 5942 5943 5944 5945 5946 5947 <div class="pubjournal"> 5948 Renewable Energy 5949 </div> 5950 5951 <div class="publinks"> 5952 5953 5954 5955 5956 5957 <a href="http://www.sciencedirect.com/science/article/pii/S0960148115303475"><i class="fas fa-external-link-alt"></i> sciencedirect.com </a> 5958 5959 5960 5961 5962 5963 5964 5965 5966 | 5967 5968 <a href="/assets/papers/La Cava et al. - 2016 - Automatic identification of wind turbine models us.pdf">pdf</a> 5969 5970 5971 </div> 5972</div> 5973 5974<div class="pubitem"> 5975 <div class="pubtitle" id="lacavaGradientbasedAdaptationContinuous2016"> 5976 Gradient-based adaptation of continuous dynamic model structures 5977 </div> 5978 <div class="pubauthors"> 5979 5980 5981 5982 5983 5984 5985 William G. La Cava and 5986 5987 5988 5989 Kourosh Danai 5990 5991 (2016) 5992 </div> 5993 5994 5995 5996 5997 5998 <div class="pubjournal"> 5999 International Journal of Systems Science 6000 </div> 6001 6002 <div class="publinks"> 6003 6004 6005 6006 6007 6008 <a href="http://www.tandfonline.com/doi/full/10.1080/00207721.2015.1069905"><i class="fas fa-external-link-alt"></i> tandfonline.com </a> 6009 6010 6011 6012 6013 6014 6015 6016 6017 | 6018 6019 <a href="/assets/papers/La Cava and Danai - 2016 - Gradient-based adaptation of continuous dynamic mo.pdf">pdf</a> 6020 6021 6022 </div> 6023</div> 6024 6025 6026 </div> 6027</div> 6028 6029 6030 </div> 6031 6032 6033 6034 <div id="footer" class="page__footer"> 6035 <footer> 6036 <!-- Parse the Latex divs with Katex--> 6037<!-- https://varunagrawal.github.io/2018/03/27/latex-jekyll/ -->
6038<script type="text/javascript"> 6039 $("script[type='math/tex']").replaceWith( 6040 function(){ 6041 var tex = $(this).text(); 6042 return katex.renderToString(tex, {displayMode: false}); 6043 }); 6044 6045 $("script[type='math/tex; mode=display']").replaceWith( 6046 function(){ 6047 var tex = $(this).text(); 6048 return katex.renderToString(tex.replace(/%.*/g, ''), {displayMode: true}); 6049 }); 6050</script>
6050 6051 6052 6053 6054 6055<div class="page__footer-follow"> 6056 <ul class="social-icons"> 6057 6058 6059 6060 6061 6062 <li><a href="mailto:[email protected]" rel="nofollow noopener noreferrer"><i class="fas fa-fw fa-envelope" aria-hidden="true"></i> Email</a></li> 6063 6064 6065 6066 <li><a href="https://github.com/cavalab" rel="nofollow noopener noreferrer"><i class="fab fa-fw fa-github" aria-hidden="true"></i> GitHub</a></li> 6067 6068 6069 6070 <li><a href="https://scholar.google.com/citations?user=iZB7inEAAAAJ&hl=en" rel="nofollow noopener noreferrer"><i class="fas fa-graduation-cap" aria-hidden="true"></i> Google Scholar</a></li> 6071 6072 6073 6074 <li><a href="https://connects.catalyst.harvard.edu/Profiles/display/Person/200560" rel="nofollow noopener noreferrer"><i class="fas fa-project-diagram" aria-hidden="true"></i> Harvard Catalyst</a></li> 6075 6076 6077 6078 <li><a href="http://chip.org" rel="nofollow noopener noreferrer"><i class="fa fa-heartbeat" aria-hidden="true"></i> CHIP</a></li> 6079 6080 6081 6082 <li><a href="https://www.childrenshospital.org/" rel="nofollow noopener noreferrer"><i class="fa fa-medkit" aria-hidden="true"></i> Boston Children's Hospital</a></li> 6083 6084 6085 6086 <li><a href="https://hms.harvard.edu/" rel="nofollow noopener noreferrer"><i class="fa fa-university" aria-hidden="true"></i> Harvard Medical School</a></li> 6087 6088 6089 6090 <li><a href="https://bsky.app/profile/lacava.bsky.social" rel="nofollow noopener noreferrer"><i class="far fa-comment" aria-hidden="true"></i> Bluesky</a></li> 6091 6092 6093 6094 6095 6096 </ul> 6097</div> 6098 6099 6100<div class="page__footer-copyright">© 2026 <a href="https://cavalab.github.io">CAVA Lab</a>. Powered by <a href="https://jekyllrb.com" rel="nofollow">Jekyll</a> & <a href="https://mademistakes.com/work/jekyll-themes/minimal-mistakes/" rel="nofollow">Minimal Mistakes</a>.</div> 6101 6102 </footer> 6103 </div> 6104 6105 6106 6107
6107<script src="/assets/js/main.min.js"></script>
6107 6108 6109 6110 6111 6112 6113 6114 6115 <!-- Global site tag (gtag.js) - Google Analytics -->
vendor: 64 bytes, lines 6115-6116
6115 6116<script async src="https://www.googletagmanager.com/gtag/js?id=
6116G-8CVW0XBQDT
vendor: 12 bytes, line 6116
6116"></script>
6117<script> 6118
vendor: 134 bytes, lines 6118-6122
6118window.dataLayer = window.dataLayer || []; 6119 function gtag(){dataLayer.push(arguments);} 6120 gtag('js', new Date()); 6121 6122 gtag('config', '
6122G-8CVW0XBQDT
vendor: 29 bytes, line 6122
6122', { 'anonymize_ip': true});
6123</script>
6123 6124 6125 6126 6127 6128 6129 6130 6131 6132 6133 </body> 6134</html>
Line numbers count LF bytes from the start of the resource, as the search results do. Vendor segments are library code the classifier recognised; they are stored but not indexed. Bytes are shown as Latin1 characters, one per byte.