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Effective sample size for individual risk predictions: quantifying uncertainty in machine learning models.

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Title: Effective sample size for individual risk predictions: quantifying uncertainty in machine learning models.
Authors: Thomassen D; Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands. Electronic address: d.thomassen@lumc.nl., Hackmann T; Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands., Goeman J; Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands., Steyerberg E; Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands., le Cessie S; Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands; Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, Netherlands.
Source: The Lancet. Digital health [Lancet Digit Health] 2025 Nov; Vol. 7 (11), pp. 100911. Date of Electronic Publication: 2025 Nov 29.
Publication Type: Journal Article; Review
Journal Info: Publisher: Elsevier Ltd Country of Publication: England NLM ID: 101751302 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2589-7500 (Electronic) Linking ISSN: 25897500 NLM ISO Abbreviation: Lancet Digit Health Subsets: MEDLINE
Database: MEDLINE Ultimate
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  Data: <searchLink fieldCode="AU" term="%22Thomassen+D%22">Thomassen D</searchLink>; Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands. Electronic address: d.thomassen@lumc.nl.<br /><searchLink fieldCode="AU" term="%22Hackmann+T%22">Hackmann T</searchLink>; Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands.<br /><searchLink fieldCode="AU" term="%22Goeman+J%22">Goeman J</searchLink>; Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands.<br /><searchLink fieldCode="AU" term="%22Steyerberg+E%22">Steyerberg E</searchLink>; Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands.<br /><searchLink fieldCode="AU" term="%22le+Cessie+S%22">le Cessie S</searchLink>; Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands; Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, Netherlands.
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  Data: <searchLink fieldCode="JN" term="%22101751302%22">The Lancet. Digital health</searchLink> [Lancet Digit Health] 2025 Nov; Vol. 7 (11), pp. 100911. <i>Date of Electronic Publication: </i>2025 Nov 29.
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  Data: <i>Publisher: </i><searchLink fieldCode="PB" term="%22Elsevier+Ltd%22">Elsevier Ltd </searchLink><i>Country of Publication: </i>England <i>NLM ID: </i>101751302 <i>Publication Model: </i>Print-Electronic <i>Cited Medium: </i>Internet <i>ISSN: </i>2589-7500 (Electronic) <i>Linking ISSN: </i><searchLink fieldCode="IS" term="%2225897500%22">25897500 </searchLink><i>NLM ISO Abbreviation: </i>Lancet Digit Health <i>Subsets: </i>MEDLINE
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        Value: 10.1016/j.landig.2025.100911
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        Text: English
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              Text: 2025 Nov
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