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An Interpretable Machine Learning Model for Early Multitemporal Prediction of Onset of Acute Kidney Injury in Intensive Care Unit Patients with Severe Trauma.

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Title: An Interpretable Machine Learning Model for Early Multitemporal Prediction of Onset of Acute Kidney Injury in Intensive Care Unit Patients with Severe Trauma.
Authors: Gao B; School of Public Health, Research Center for Medicine and Social Development, Innovation Center for Social Risk Governance in Health, Research Center for Public Health Security, First Affiliated Hospital, Chongqing Medical University, Chongqing, China., Jin H; School of Public Health, Research Center for Medicine and Social Development, Innovation Center for Social Risk Governance in Health, Research Center for Public Health Security, First Affiliated Hospital, Chongqing Medical University, Chongqing, China., Zhang Y; School of Public Health, Research Center for Medicine and Social Development, Innovation Center for Social Risk Governance in Health, Research Center for Public Health Security, First Affiliated Hospital, Chongqing Medical University, Chongqing, China., Chen J; School of Public Health, Research Center for Medicine and Social Development, Innovation Center for Social Risk Governance in Health, Research Center for Public Health Security, First Affiliated Hospital, Chongqing Medical University, Chongqing, China.; The Simpson Centre for Health Services Research, Faculty of Medicine, University of New South Wales, Sydney, NSW, Australia.
Source: Journal of intensive care medicine [J Intensive Care Med] 2026 Jul; Vol. 41 (7), pp. 630-642. Date of Electronic Publication: 2025 Oct 29.
Publication Type: Journal Article
Journal Info: Publisher: Sage Publications Country of Publication: United States NLM ID: 8610344 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1525-1489 (Electronic) Linking ISSN: 08850666 NLM ISO Abbreviation: J Intensive Care Med Subsets: MEDLINE
Database: MEDLINE Ultimate
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ISSN:1525-1489
DOI:10.1177/08850666251390848