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

Internet

https://scholarbank.nus.edu.sg/handle/10635/217001

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