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

Computer-Aided Diagnosis (135) Artificial Intelligence (1421) Machine Learning (1501) Electronic Health Records (1068) Decision Support for Health Professionals (1210) Clinical Information and Decision Making (1434) Clinical Informatics (1050)

Published on in Vol 12 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/48862, first published .
Interpretable Deep Learning System for Identifying Critical Patients Through the Prediction of Triage Level, Hospitalization, and Length of Stay: Prospective Study

Interpretable Deep Learning System for Identifying Critical Patients Through the Prediction of Triage Level, Hospitalization, and Length of Stay: Prospective Study

Interpretable Deep Learning System for Identifying Critical Patients Through the Prediction of Triage Level, Hospitalization, and Length of Stay: Prospective Study

Authors of this article:

Yu-Ting Lin1 Author Orcid Image ;   Yuan-Xiang Deng1 Author Orcid Image ;   Chu-Lin Tsai2 Author Orcid Image ;   Chien-Hua Huang2 Author Orcid Image ;   Li-Chen Fu1 Author Orcid Image
Article Authors Cited by (1) Tweetations (2) Metrics

Journals

  1. Ganatra H, Latifi S, Baloglu O. Pediatric Intensive Care Unit Length of Stay Prediction by Machine Learning. Bioengineering 2024;11(10):962 View