Machine Learning for Predicting Risk and Prognosis of Acute Kidney Disease in Critically Ill Elderly Patients During Hospitalization: Internet-Based and Interpretable Model Study

• Main Authors: Mingxia Li (Author), Shuzhe Han (Author), Fang Liang (Author), Chenghuan Hu (Author), Buyao Zhang (Author), Qinlan Hou (Author), Shuangping Zhao (Author)
• Format: Book
• Published: JMIR Publications, 2024-05-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.

BackgroundAcute kidney disease (AKD) affects more than half of critically ill elderly patients with acute kidney injury (AKI), which leads to worse short-term outcomes. ObjectiveWe aimed to establish 2 machine learning models to predict the risk and prognosis of AKD in the elderly and to deploy the...