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

Clinical Information and Decision Making (1686) Decision Support for Health Professionals (1361) Artificial Intelligence (1775) Outbreak and Pandemic Preparedness and Management (1784) Infectious Diseases (non-STD/STI) (1659) Machine Learning (1770) Advanced Data Analytics in eHealth (169)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/52134, first published .
Development and Validation of a Robust and Interpretable Early Triaging Support System for Patients Hospitalized With COVID-19: Predictive Algorithm Modeling and Interpretation Study

Development and Validation of a Robust and Interpretable Early Triaging Support System for Patients Hospitalized With COVID-19: Predictive Algorithm Modeling and Interpretation Study

Development and Validation of a Robust and Interpretable Early Triaging Support System for Patients Hospitalized With COVID-19: Predictive Algorithm Modeling and Interpretation Study

Authors of this article:

Sangwon Baek1, 2 Author Orcid Image ;   Yeon joo Jeong3 Author Orcid Image ;   Yun-Hyeon Kim4 Author Orcid Image ;   Jin Young Kim5 Author Orcid Image ;   Jin Hwan Kim6 Author Orcid Image ;   Eun Young Kim7 Author Orcid Image ;   Jae-Kwang Lim8 Author Orcid Image ;   Jungok Kim9 Author Orcid Image ;   Zero Kim1, 10 Author Orcid Image ;   Kyunga Kim10, 11, 12 Author Orcid Image ;   Myung Jin Chung1, 10, 12, 13 Author Orcid Image
Article Authors Cited by (1) Tweetations (4) Metrics

Journals

  1. Li Y, Xiao M, Li Y, Lv L, Zhang S, Liu Y, Zhang J. Machine Learning for the Prediction of Acute Kidney Injury in Critically Ill Patients With Coronary Heart Disease: Algorithm Development and Validation. JMIR Medical Informatics 2025;13:e72349 View