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

Decision Support for Health Professionals (1181) Artificial Intelligence (1363) Machine Learning (1459) Clinical Information and Decision Making (1401) Perioperative Risk Assessment (14) Artificial Intelligence in Surgery and Perioperative Medicine (27)

Published on in Vol 9, No 9 (2021): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/31311, first published .
Short-Term Event Prediction in the Operating Room (STEP-OP) of Five-Minute Intraoperative Hypotension Using Hybrid Deep Learning: Retrospective Observational Study and Model Development

Short-Term Event Prediction in the Operating Room (STEP-OP) of Five-Minute Intraoperative Hypotension Using Hybrid Deep Learning: Retrospective Observational Study and Model Development

Short-Term Event Prediction in the Operating Room (STEP-OP) of Five-Minute Intraoperative Hypotension Using Hybrid Deep Learning: Retrospective Observational Study and Model Development

Authors of this article:

Sooho Choe1 Author Orcid Image ;   Eunjeong Park2 Author Orcid Image ;   Wooseok Shin3 Author Orcid Image ;   Bonah Koo4 Author Orcid Image ;   Dongjin Shin5 Author Orcid Image ;   Chulwoo Jung6 Author Orcid Image ;   Hyungchul Lee6 Author Orcid Image ;   Jeongmin Kim7 Author Orcid Image
Article Authors Cited by (8) Tweetations (4) Metrics

Sooho Choe   1 * ;   Eunjeong Park   2 * , PhD ;   Wooseok Shin   3 , MSc ;   Bonah Koo   4 , BSc ;   Dongjin Shin   5 ;   Chulwoo Jung   6 , MD, PhD ;   Hyungchul Lee   6 , MD, PhD ;   Jeongmin Kim   7 , MD

1 School of Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea

2 Cerebro-Cardiovascular Research Institute, Yonsei University College of Medicine, Seoul, Republic of Korea

3 School of Industrial and Management Engineering, Korea University, Seoul, Republic of Korea

4 SK Inc C&C, Seoul, Republic of Korea

5 School of Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea

6 Department of Anesthesiology and Pain Medicine, Seoul National University, Seoul National University Hospital, Seoul, Republic of Korea

7 Department of Anesthesiology and Pain Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea

*these authors contributed equally

Corresponding Author:

  • Jeongmin Kim, MD
  • Department of Anesthesiology and Pain Medicine
  • Yonsei University College of Medicine
  • 50 Yonsei-ro
  • Seodaemungu
  • Seoul, 03722
  • Republic of Korea
  • Phone: 82 2-2228-6456
  • Fax: 82 2-312-7185
  • Email: Anesjeongmin@yuhs.ac