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Fairness, Performance, and Interpretability of NMDoH Predictive Models: Composite AI Modeling
Jiefei Wang;
Weibin Zhang;
Monique Pappadis;
Susanne Schmidt;
Zhanwei Wang;
Vibhuti Gupta;
Christopher Kulesza;
Erich Kummerfeld;
Rodney Hunter;
Suresh K. Bhavnani
ABSTRACT
Composite AI modeling that integrates results from bipartite network, pooled, stratified predictive models can address fairness among patient subgroups while being interpretable when predicting depression among cancer patients.
Citation
Please cite as:
Wang J, Zhang W, Pappadis M, Schmidt S, Wang Z, Gupta V, Kulesza C, Kummerfeld E, Hunter R, Bhavnani SK
Fairness, Performance, and Interpretability of NMDoH Predictive Models: Composite AI Modeling