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Updated: Jul 2, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
Assessing a Bayesian risk prediction model in a high-risk breast cancer population
Jennifer Chun1, Freya Schnabel, Omolola Ogunyemi
1Department of Surgery, Comprehensive Breast Center, Women At Risk, New Yourk Presbyterian Hospital, Columbea University Medical Center, New Yourk, NY, USA.
Abstract:
The purpose of this study was to utilize a Bayesian risk prediction model to predict the incidence of breast cancer in a high risk population. 10-fold cross-validation was performed using a Naïve Bayes classifier. The area under the ROC curve (AUC) was used to measure prediction accuracy. These results were then compared to the ROC curve (AUC) results of the Gail Model Risk Assessment Tool.
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