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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Direct Uncertainty Prediction for Medical Second Opinions · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/1807.01771/</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/1807.01771/feed.xml" rel="self" type="application/rss+xml" /><item><title>Direct Uncertainty Prediction for Medical Second Opinions — mentioned by MAXPOOL</title><link>https://news.ycombinator.com/item?id=19045987</link><guid isPermaLink="false">urn:hackerpapers:mention:1807.01771:19045987</guid><pubDate>Thu, 31 Jan 2019 16:30:20 GMT</pubDate><description>&lt;p&gt;Not my exact field, but I keep track of the research for potential applications. The general vibe is that there are potentially large welfare gains to be achieved if algorithms, ML or statistical methods are integrated into human decision making in principled way. People have innate tendency treat noise as a signal. That does not mean that the dangers mentioned in the article are not real [2]. We should be very aware of them in their current forms and prevent repeating them. Few of my favorite papers: 1. Human Decisions and Machine Predictions The Quarterly Journal of Economics, Volume 133…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/1807.01771/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item></channel></rss>
