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This paper is in the following e-collection/theme issue:

Machine Learning (3053) Big Data (426) Decision Support for Health Professionals (2121) Coronary Heart Disease (150) Cardiac Risk and Cardiac Risk Calculators (165) Artificial Intelligence (4543) Nephrology/Renal Disorders (134)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/72349, first published .
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Machine Learning for the Prediction of Acute Kidney Injury in Critically Ill Patients With Coronary Heart Disease: Algorithm Development and Validation

Machine Learning for the Prediction of Acute Kidney Injury in Critically Ill Patients With Coronary Heart Disease: Algorithm Development and Validation

Authors of this article:

Yike Li1 Author Orcid Image ;   Mingyang Xiao1 Author Orcid Image ;   Yaqian Li1 Author Orcid Image ;   Lulu Lv1 Author Orcid Image ;   Shanshan Zhang1 Author Orcid Image ;   Yuhui Liu1 Author Orcid Image ;   Juan Zhang1 Author Orcid Image
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Journals

  1. Garcés M, García J, Montoya J, Triana C, Hernández Rincón E. Artificial intelligence-based models for clinical prognosis at the end of life in the ICU. International Journal of Medical Informatics 2026;206:106156 View
  2. Guo D, Bai J, Zhang J, Xi X, Chen Y, Luo Z, Feng K, Zeng J, Zhang M, Dong W, Xu X, Wang R, Zhang Y. Multicenter validation of an explainable machine learning model for early prediction of acute kidney injury in critically ill patients with digestive system tumors. DIGITAL HEALTH 2026;12 View