Article

Explainable machine learning for clinical phenotyping and mortality prediction in critically ill patients with cancer

2026-08-27

Abstract excerpt

<title>Abstract</title> <p>Critically ill patients with cancer are clinically heterogeneous, limiting the prognostic performance of conventional severity scores. This multicenter retrospective study used MIMIC-IV for model derivation and the eICU Collaborative Research Database for external validation to identify data-driven clinical phenotypes and develop an explainable machine learning model for early in-hospit...

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Literature Corpus work: 4b6094cb-aa86-5973-a418-d0e6d5f3284c
DOI: 10.21203/rs.3.rs-10215545/v1

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