Health Care Analytics With Time-Invariant and Time-Variant Feature Importance to Predict Hospital-Acquired Acute Kidney Injury: Observational Longitudinal Study

Health Care Analytics With Time-Invariant and Time-Variant Feature Importance to Predict Hospital-Acquired Acute Kidney Injury: Observational Longitudinal Study

10.2196/30805

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Bibliographic Details
Main Authors:	Chua, Horng-Ruey, Zheng, Kaiping, Vathsala, Anantharaman, Ngiam, Kee-Yuan, Yap, Hui-Kim, Lu, Liangjian, Tiong, Ho-Yee, Mukhopadhyay, Amartya, MacLaren, Graeme, Lim, Shir-Lynn, Akalya, K, Ooi, Beng-Chin
Other Authors:	DEPARTMENT OF COMPUTER SCIENCE
Format:	Article
Language:	English
Published:	JMIR PUBLICATIONS, INC 2022
Subjects:	Science & Technology Life Sciences & Biomedicine Health Care Sciences & Services Medical Informatics acute kidney injury artificial intelligence biomarkers clinical deterioration electronic health records hospital medicine machine learning CONTRAST-INDUCED NEPHROPATHY INTERVENTION PROGRAM TRENDS
Online Access:	https://scholarbank.nus.edu.sg/handle/10635/217001
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Institution:	National University of Singapore
Language:	English

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Summary:	10.2196/30805