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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Inferring Which Medical Treatments Work from Reports of Clinical Trials · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1904.01606/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/1904.01606/feed.xml" rel="self" type="application/rss+xml" /><item><title>Inferring Which Medical Treatments Work from Reports of Clinical Trials — mentioned by jdjayded</title><link>https://news.ycombinator.com/item?id=20480331</link><guid isPermaLink="false">urn:hackerpapers:mention:1904.01606:20480331</guid><pubDate>Fri, 19 Jul 2019 16:53:50 GMT</pubDate><description>&lt;p&gt;I&amp;#x27;m a little late to this party, but here&amp;#x27;s a mandatory research plug: My lab works in the area of evidence based medicine. My research focuses on Randomized Controlled Trials, and the overall goal is to automate (fully or partially) the meta-analysis of medical interventions. To that end, we collected a dataset of intervention pairs, statistical significance findings about these pairs, and a minimal rationale supporting the significance finding. Since these annotations were collected on full text PubMed Open Access articles, we can distribute both the articles and the annotations…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1904.01606/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item></channel></rss>
