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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Generative Medical Event Models Improve with Scale · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2508.12104/</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/2508.12104/feed.xml" rel="self" type="application/rss+xml" /><item><title>Generative Medical Event Models Improve with Scale — mentioned by brendanashworth</title><link>https://news.ycombinator.com/item?id=46222677</link><guid isPermaLink="false">urn:hackerpapers:mention:2508.12104:46222677</guid><pubDate>Wed, 10 Dec 2025 19:46:58 GMT</pubDate><description>&lt;p&gt;Would a wearable model like this gain in predictive power by adding FHIR/EHR inputs? CoMET [1] has great AUC even without daily/lifestyle metrics like steps, awakenings at night, or vo2max estimates (which are present in say apple health). It would be interesting to know how much you would gain from having a holistic model that sees both inputs. [1] https://arxiv.org/pdf/2508.12104v1&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2508.12104/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item><item><title>Generative Medical Event Models Improve with Scale — HN submission</title><link>https://news.ycombinator.com/item?id=44971660</link><guid isPermaLink="false">urn:hackerpapers:submission:2508.12104:44971660</guid><pubDate>Thu, 21 Aug 2025 11:59:44 GMT</pubDate><description>&lt;p&gt;Scaling laws found in large generative medical event models&lt;/p&gt;&lt;p&gt;&lt;/p&gt;&lt;p&gt;1 point; 0 discussion replies on HN. &lt;a href="https://hackerpaper.kaipfister.de/p/2508.12104/"&gt;Paper and source history&lt;/a&gt;. A submission is not an endorsement.&lt;/p&gt;</description><category>cs.LG</category></item></channel></rss>
