A Simplified Metric to Streamline Between-Group Fairness Assessment for Predictive Models: Algorithm Development and Evaluation Study.

Haoyuan Wang¹, Chuan Hong¹, Michael Pencina¹, Matthew Engelhard¹

¹Department of Biostatistics and Bioinformatics, Duke University School of Medicine, 2424 Erwin Rd, Durham, NC, 27705, United States, 1 919-613-3665.

PubMed DOI

Abstract

BACKGROUND: Fairness evaluation is essential for trustworthy clinical risk prediction. However, existing fairness-oriented discrimination metrics either ignore cross-group comparisons or rely on exhaustive pairwise evaluations, making them difficult to interpret and impractical for model selection. OBJECTIVE: This study aimed to develop and evaluate novel fairness-oriented discrimination metrics…

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