Uncertainty in Breast Cancer Risk Prediction: A Conformai Prediction Study of Race Stratification...19th World Congress on Medical and Health Informatics, July 8-12, 2023, New South Wales.
The use of Artificial Intelligence (AI) in medicine has attracted a great deal of attention in the medical literature, but less is known about how to assess the uncertainty of individual predictions in clinical applications. This paper demonstrates the use of Conformal Prediction (CP) to provide ins...
| Publicado en: | Studies in Health Technology & Informatics Vol. 310; pp. 991 - 996 |
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| Autores principales: | , , , |
| Formato: | proceedings research tables/charts Journal Article |
| Publicado: |
Sage Publications Inc.
2023
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=175248923&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 175248923 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09269630 U1V jtl: Studies in Health Technology & Informatics issn: 09269630 maglogo: N pubinfo: dt: 2023 vid: 310 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 175248923 175248923 175248923 10.3233/SHTI231113 175248923 ppf: 991 ppct: 5 formats: tig: atl: Uncertainty in Breast Cancer Risk Prediction: A Conformai Prediction Study of Race Stratification...19th World Congress on Medical and Health Informatics, July 8-12, 2023, New South Wales. aug: au: Millar, Alexander S. Arnn, John Himes, Sam Facelli, Julio C. affil: Department of Biomedical Informatics and Clinical and Translational Science Institute, The University of Utah, Salt Lake City, UT 84108, USA sug: subj: Breast Neoplasms Risk Factors Uncertainty Prediction Models Racism Artificial Intelligence Risk Assessment Human Congresses and Conferences New South Wales New South Wales Machine Learning Descriptive Statistics Comparative Studies Funding Source ab: The use of Artificial Intelligence (AI) in medicine has attracted a great deal of attention in the medical literature, but less is known about how to assess the uncertainty of individual predictions in clinical applications. This paper demonstrates the use of Conformal Prediction (CP) to provide insight on racial stratification of uncertainty quantification for breast cancer risk prediction. The results presented here show that CP methods provide important information about the diminished quality of predictions for individuals of minority racial backgrounds. pubtype: Academic Journal doctype: proceedings research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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