Interpretable machine learning models for predicting in-hospital mortality in patients with chronic critical illness and heart failure: A multicenter study

Interpretable machine learning models for predicting in-hospital mortality in patients with chronic critical illness and heart failure: A multicenter study

Background Heart failure (HF) is a primary contributor to morbidity and mortality among patients in intensive care units (ICUs), particularly those experiencing chronic critical illness (CCI). This study aims to develop and validate a machine learning (ML) model for predicting in-hospital mortality...

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Main Authors: Min He, Yongqi Lin, Siyu Ren, Pengzhan Li, Guoqing Liu, Liangbo Hu, Xueshuang Bei, Lingyan Lei, Yue Wang, Qianghong Zhang, Xiaocong Zeng
Format: Article
Language:English
Published: SAGE Publishing 2025-06-01
Series:Digital Health
Online Access:https://doi.org/10.1177/20552076251347785
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https://doi.org/10.1177/20552076251347785

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