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233                <h1 class="posttitle">Keeping up with scientific literature</h1>
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256                <p>The march of scientific progress waits for no-one. This is what makes what we do
257exciting, but also at times overwhelming. It has been rightly noted that
258<a href="https://www.sciencemag.org/careers/2016/11/how-keep-scientific-literature">keeping up with literature can be a bit of a chore, and even at times disheartening</a>,
259if we find the exciting ideas we are pursuing have been done before. And yet,
260my PhD supervisor’s words echo in my head, “an hour in the library could save
261you a week in the lab.” He has been correct many times.</p>
262
263<p>In order for research to have impact, it must fit its audience, context,
264and scope. This requires a good understanding of the surrounding scientific
265literature. Putting aside the fact that reading academic articles is a
266skill requiring deliberate practice and patient persistence, today’s
267academic may find themselves deluged by the sheer volume of published
268research. At the start of medical school, I was told that studying
269medicine would be like drinking from a fire hydrant. This is doubly true
270of research, except you cannot be sure when the stream ends or if you are
271even at the right hydrant. Knowledge and established paradigms
272become outdated so quickly that they often feel like passing fads.</p>
273
274<p>I’d like to review some methods that I’ve personally tried to stay on
275top of things. I’ll also go into the latest method
276I’ve been trying, which makes use of the
277<a href="http://scireader.org/">SciReader</a> recommender engine.</p>
278
279<h2 id="what-ive-tried">What I’ve tried</h2>
280
281<p>In my search to tame the information torrent, I came across the
282<a href="https://fraserlab.com/2013/09/28/The-Fraser-Lab-method-of-following-the-scientific-literature/">Fraser Lab method at UCSF</a>.
283In short, they endorse the use of RSS feeds browsed with a central
284app such as <a href="https://feedly.com/">Feedly</a> or <a href="https://www.inoreader.com/">InoReader</a>.
285This method saw me through the last half of my PhD, and often made me
286the first among my peers to come across relevant new papers.
287Over a few years, I built up a list of over 600 papers of interest.
288The downside was the upkeep. Working in an interdisciplinary
289field, I needed to keep abreast of papers from a wide range of journals,
290and screening the titles of hundreds of articles for a
291handful of relevant ones became tedious. I would fall behind whenever
292deadlines loomed, and after returning to the clinical world,
293this method fell by the wayside.</p>
294
295<p>What became more useful were the few <a href="https://www.nlm.nih.gov/bsd/disted/pubmedtutorial/040_060.html">PubMed search alerts I had set up</a>.
296This approach has better specificity, but poor sensitivity,
297which can make it difficulty to discover work in complementary fields.
298Alternatively, you could use the <a href="http://pubcrawler.gen.tcd.ie/">PubCrawler web service</a>
299to have matching articles emailed to you.</p>
300
301<h2 id="do-machine-learning-to-it">Do Machine Learning to it</h2>
302
303<p>Enter SciReader. As described on the bioRxiv, it is a cloud-based personalized recommender system
304that uses topic modeling and machine learning. Give it a list of papers or topics of interest
305 and it will return an evolving list of recommended articles. This sounded familiar to me,
306as I used a similar service called PubChase, which unfortunately closed down a few years ago.
307But given my struggles, I was willing to give the concept another try.</p>
308
309<p>I created a SciReader account and entered some preliminary information about topics of interest
310and my own publication list. SciReader takes roughly a day to generate recommendations for you.</p>
311
312<p>SciReader’s parameterization of manuscripts considers article content,
313metrics of paper quality and relevance, and the activity of other users with similar interests.
314It performs topic modeling on the complete pubmed corpus by latent dirichlet allocation on the
315TF-IDF metric with a cosine distance metric. One potential limitation is that it matches
316based on abstracts only, as full text often sits behind a paywall. This may obscure
317papers containing findings of interest buried in the results section, but for the
318most part should suffice for most users.</p>
319
320<h2 id="detour-exporting-articles-from-feedly">Detour: Exporting Articles from Feedly</h2>
321
322<p>For those wanting a jumpstart, you can export citations from EndNote or Mendeley in BibTeX format
323and import them. However, as someone who’s changed research fields a few times, and has used
324these tools to write numerous course papers, I recognized that this would introduce many
325unrelated topics into the system.</p>
326
327<p>Instead, I turned to my Feedly “Read Later” list, which contained some 700 articles I had specifically
328flagged as interesting to me. With some javascript magic, I scraped the titles, sources, and URLs of
329every paper I’d flagged. I filtered these to contain only research articles.</p>
330
331<p>In order to import into Feedly, I needed to convert this data into
332<a href="http://www.bibtex.org/Format/">BibTeX format</a>,
333which at least requires the author list, year, and journal.
334Luckily, Google Scholar has the handy ability to find almost any
335article by its title alone, and
336helpfully generates citations in BibTeX format. Using a
337<a href="https://selenium-python.readthedocs.io/">Python Selenium</a> script, I was able to automate the
338process of pulling down the hundreds of articles in BibTeX format (much to the Google CAPTCHA’s
339chagrin, but I don’t think I caused any damage). Perhaps someone knows a better
340way to rapidly convert a set of journal article titles into citations.
341I then verified that Google Scholar’s resulting articles matched
342my chosen articles with some fuzzy string matching, using one of my favorite packages
343<a href="https://github.com/seatgeek/fuzzywuzzy">FuzzyWuzzy</a>. This gave me a unified BibTeX file to
344upload into SciReader.</p>
345
346<p>I’ve put the code I used into a <a href="https://github.com/eyzhao/feedly-to-scireader">GitHub repo</a>.
347The documentation is admittedly sparse, but it might serve as a launching-off point
348for someone who wants to do something similar.</p>
349
350<h2 id="the-verdict">The Verdict</h2>
351
352<p>SciReader’s engine recommended numerous recent publications clearly linked to my personal area of
353interest and expertise. It captures results from a wide range of journals. It also does a great
354job highlighting groundbreaking recent advances in fields adjacent to my own. I suspect this
355is the combination of topic modeling, quality assessment, and collaborative filtering at work.
356It might take a little while for me to get a full sense of how well this system works for me,
357so I will report back down the road.</p>
358
359<p>The site itself can be buggy at times. In particular, I found the “Load more” button 
360(which shows you more recommendations) would sometimes not work, requiring a page reload.
361Also, during the month of March 2020, the site seemed to be down altogether - I’m not sure
362who is maintaining it presently.</p>
363
364<p>All in all, this is what I would consider a hacked-together approach to give me one
365more angle of attack when it comes to dealing with the research literature glut.
366Whether it translates into actionable insights, I don’t know. But it’s gotten me to
367think more about how I stay on top of my reading.</p>
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