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Uncertainty in Breast Cancer Risk Prediction: A Conformal Prediction Study of Race Stratification
Alexander S. Millar, John Arnn, Sam Himes, Julio C. Facelli
991 - 995
10.3233/SHTI231113
Research Article
Studies in Health Technology and Informatics
Volume 310: MEDINFO 2023 — The Future Is Accessible
Abstract

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.

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