Explainable AI for analyzing cancer outcomes using large-scale genome sequencing data
A multi-tier, explainable AI framework designed to risk-stratify patients and predict overall survival using clinical and genomic covariates is developed and demonstrates that explainable machine learning models can robustly predict survivability and highlight actionable features for oncology dashboards.
P. Nalela
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