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: | , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2025-06-01
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| Series: | Digital Health |
| Online Access: | https://doi.org/10.1177/20552076251347785 |
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