A Machine-Learned Comorbidity Index

In three linesMachine-Learned Comorbidity Index (MLCI) maps diagnosis codes to a single scalar by maximizing normalized Hilbert-Schmidt Independence Criterion across multiple clinical outcomes. Unlike traditional indices (Charlson, Elixhauser), MLCI captures nonlinear risk-outcome relationships and outperforms baselines on multiple EHR datasets.

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