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

Clinical Information and Decision Making (1407) Decision Support for Health Professionals (1185) Artificial Intelligence (1371) Machine Learning (1465) Cardiology (159)

Published on in Vol 23, No 7 (2021): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28361, first published .
Developing a Time-Adaptive Prediction Model for Out-of-Hospital Cardiac Arrest: Nationwide Cohort Study in Korea

Developing a Time-Adaptive Prediction Model for Out-of-Hospital Cardiac Arrest: Nationwide Cohort Study in Korea

Developing a Time-Adaptive Prediction Model for Out-of-Hospital Cardiac Arrest: Nationwide Cohort Study in Korea

Authors of this article:

Ji Woong Kim1 Author Orcid Image ;   Juhyung Ha2 Author Orcid Image ;   Taerim Kim3 Author Orcid Image ;   Hee Yoon3 Author Orcid Image ;   Sung Yeon Hwang3 Author Orcid Image ;   Ik Joon Jo3 Author Orcid Image ;   Tae Gun Shin3 Author Orcid Image ;   Min Seob Sim3 Author Orcid Image ;   Kyunga Kim1, 4 Author Orcid Image ;   Won Chul Cha1, 3, 5 Author Orcid Image
Article Authors Cited by (5) Tweetations (2) Metrics

Ji Woong Kim   1 , MS ;   Juhyung Ha   2 , MSc ;   Taerim Kim   3 , MD ;   Hee Yoon   3 , MD ;   Sung Yeon Hwang   3 , MD ;   Ik Joon Jo   3 , MD ;   Tae Gun Shin   3 , MD ;   Min Seob Sim   3 , MD ;   Kyunga Kim   1, 4 , PhD ;   Won Chul Cha   1, 3, 5 , MD

1 Department of Digital Health, Samsung Advanced Institute for Health Science & Technology, Sungkyunkwan University, Seoul, Republic of Korea

2 Department of Computer Science, Indiana University, Bloomington, IN, United States

3 Department of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea

4 Statistics and Data Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul, Republic of Korea

5 Health Information and Strategy Center, Samsung Medical Center, Seoul, Republic of Korea

Corresponding Author:

  • Won Chul Cha, MD
  • Department of Digital Health
  • Samsung Advanced Institute for Health Science & Technology
  • Sungkyunkwan University
  • 115, Irwon-ro, Gangnam-gu, Seoul, Republic of Korea
  • Seoul
  • Republic of Korea
  • Phone: 82 2-3410-2053
  • Fax: 82 2-3410-0012
  • Email: docchaster@gmail.com