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

Decision Support for Health Professionals (1460) Cardiac Risk and Cardiac Risk Calculators (91) Electronic Health Records (1267) Machine Learning (1952) Tools, Programs and Algorithms (356) Artificial Intelligence (1983)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/72232, first published .
Deep Learning–Based Early Warning Systems in Hospitalized Patients at Risk of Code Blue Events and Length of Stay: Retrospective Real-World Implementation Study

Deep Learning–Based Early Warning Systems in Hospitalized Patients at Risk of Code Blue Events and Length of Stay: Retrospective Real-World Implementation Study

Deep Learning–Based Early Warning Systems in Hospitalized Patients at Risk of Code Blue Events and Length of Stay: Retrospective Real-World Implementation Study

Authors of this article:

Ji-hyun Kim1 Author Orcid Image ;   Eun Young Cho1 Author Orcid Image ;   Yuhyun Choi1 Author Orcid Image ;   Joo-Yun Won1 Author Orcid Image ;   Se Hee Cheon2 Author Orcid Image ;   Young Ae Kim3 Author Orcid Image ;   Ki-byung Lee1, 4 Author Orcid Image ;   Kwang Joon Kim1, 5 Author Orcid Image ;   Ho Gwan Kim6 Author Orcid Image ;   Taeyong Sim1 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Ji-hyun Kim   1 * , PhD ;   Eun Young Cho   1 * , PhD ;   Yuhyun Choi   1 , RN ;   Joo-Yun Won   1 , PhD ;   Se Hee Cheon   2 , RN ;   Young Ae Kim   3 , BSc ;   Ki-byung Lee   1, 4 , MD ;   Kwang Joon Kim   1, 5 , MD ;   Ho Gwan Kim   6 * , MD ;   Taeyong Sim   1 * , MD

1 AITRICS Corp, Seoul, Republic of Korea

2 Department of Medical Management, Presbyterian Medical Center, Jeonju, Republic of Korea

3 Department of Computing Information, Presbyterian Medical Center, Jeonju, Republic of Korea

4 Department of Internal Medicine, Chuncheon Sacred Heart Hospital, Chuncheon, Republic of Korea

5 Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea

6 Department of Emergency Medicine, Presbyterian Medical Center, Jeonju, Republic of Korea

*these authors contributed equally

Corresponding Author:

  • Taeyong Sim, MD
  • AITRICS Corp
  • 218 Teheran-ro, Gangnam-gu
  • Seoul 06221
  • Republic of Korea
  • Phone: 82 025695507
  • Fax: 82 025695508
  • Email: tae@aitrics.com