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

Clinical Information and Decision Making (954) Electronic Health Records (810) Machine Learning (1059) Secondary Use of Clinical Data for Research and Surveillance (260) Clinical Informatics (581) Natural Language Processing (509) Tools, Programs and Algorithms (189) Artificial Intelligence (726) Big Data (174)

Published on in Vol 23 , No 12 (2021) :December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/27008, first published .
A Novel Deep Learning–Based System for Triage in the Emergency Department Using Electronic Medical Records: Retrospective Cohort Study

A Novel Deep Learning–Based System for Triage in the Emergency Department Using Electronic Medical Records: Retrospective Cohort Study

A Novel Deep Learning–Based System for Triage in the Emergency Department Using Electronic Medical Records: Retrospective Cohort Study

Authors of this article:

Li-Hung Yao 1 Author Orcid Image ;   Ka-Chun Leung 1 Author Orcid Image ;   Chu-Lin Tsai 2 Author Orcid Image ;   Chien-Hua Huang 2 Author Orcid Image ;   Li-Chen Fu 1 Author Orcid Image
Article Authors Cited by (4) Tweetations (3) Metrics

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  2. Inokuchi R, Iwagami M, Sun Y, Sakamoto A, Tamiya N. Machine learning models predicting undertriage in telephone triage. Annals of Medicine 2022;54(1):2989 View
  3. Nguyen T, Ho C, Bui H, Ho L, Ta V. Multidimensional Machine Learning for Assessing Parameters Associated With COVID-19 in Vietnam: Validation Study. JMIR Formative Research 2023;7:e42895 View
  4. Ragab M, Kateb F, Al-Rabia M, Hamed D, Althaqafi T, AL-Ghamdi A. A Machine Learning Approach for Monitoring and Classifying Healthcare Data-A Case of Emergency Department of KSA Hospitals. International Journal of Environmental Research and Public Health 2023;20(6):4794 View