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Auditor Models to Suppress Poor AI Predictions Can Improve Human-AI Collaborative Performance.

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Title: Auditor Models to Suppress Poor AI Predictions Can Improve Human-AI Collaborative Performance.
Authors: Brown KE; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee., Wrenn JO; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.; Department of Emergency Medicine, Vanderbilt University Medical Center, Nashville, Tennessee., Jackson NJ; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee., Cauley MR; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee., Collins B; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee., Novak LL; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee., Malin BA; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.; Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee.; Department of Computer Science, Vanderbilt University, Nashville, Tennessee., Ancker JS; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.
Source: MedRxiv : the preprint server for health sciences [medRxiv] 2025 Jun 24. Date of Electronic Publication: 2025 Jun 24.
Publication Type: Journal Article; Preprint
Journal Info: Country of Publication: United States NLM ID: 101767986 Publication Model: Electronic Cited Medium: Internet NLM ISO Abbreviation: medRxiv Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
FullText Text:
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PubType: Academic Journal
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  Data: Auditor Models to Suppress Poor AI Predictions Can Improve Human-AI Collaborative Performance.
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  Data: <searchLink fieldCode="AU" term="%22Brown+KE%22">Brown KE</searchLink>; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.<br /><searchLink fieldCode="AU" term="%22Wrenn+JO%22">Wrenn JO</searchLink>; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.; Department of Emergency Medicine, Vanderbilt University Medical Center, Nashville, Tennessee.<br /><searchLink fieldCode="AU" term="%22Jackson+NJ%22">Jackson NJ</searchLink>; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.<br /><searchLink fieldCode="AU" term="%22Cauley+MR%22">Cauley MR</searchLink>; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.<br /><searchLink fieldCode="AU" term="%22Collins+B%22">Collins B</searchLink>; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.<br /><searchLink fieldCode="AU" term="%22Novak+LL%22">Novak LL</searchLink>; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.<br /><searchLink fieldCode="AU" term="%22Malin+BA%22">Malin BA</searchLink>; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.; Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee.; Department of Computer Science, Vanderbilt University, Nashville, Tennessee.<br /><searchLink fieldCode="AU" term="%22Ancker+JS%22">Ancker JS</searchLink>; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.
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  Data: <searchLink fieldCode="JN" term="%22101767986%22">MedRxiv : the preprint server for health sciences</searchLink> [medRxiv] 2025 Jun 24. <i>Date of Electronic Publication: </i>2025 Jun 24.
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  Data: <i>Country of Publication: </i>United States <i>NLM ID: </i>101767986 <i>Publication Model: </i>Electronic <i>Cited Medium: </i>Internet <i>NLM ISO Abbreviation: </i>medRxiv <i>Subsets: </i>PubMed not MEDLINE
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        Value: 10.1101/2025.06.24.25330212
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              Text: 2025 Jun 24
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