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cs.LG2026
Collapsibility of Performance Metrics in Clinical Predictive AI
João Matos, Ben Van Calster, Richard D. Riley +2
Background: Population level assessments of predictive artificial intelligence (AI) can conceal performance disparities across subgroups. Fairness evaluations commonly rely on perf…
stat.ME2026
Incorporating Missing Data Considerations into Sample Size Calculations for Developing Clinical Prediction Models
Glen P. Martin, Sian Bladon, Rebecca Whittle +3
Clinical prediction models must be developed using sufficiently large datasets to minimise overfitting and ensure robust predictive performance. Existing sample size calculations a…