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

Artificial Intelligence (1216) Natural Language Processing (650) Clinical Information and Decision Making (1340) Machine Learning (1401) Clinical Informatics (919) Decision Support for Health Professionals (1147)

Published on in Vol 24, No 12 (2022): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/43757, first published .
Model for Predicting In-Hospital Mortality of Physical Trauma Patients Using Artificial Intelligence Techniques: Nationwide Population-Based Study in Korea

Model for Predicting In-Hospital Mortality of Physical Trauma Patients Using Artificial Intelligence Techniques: Nationwide Population-Based Study in Korea

Model for Predicting In-Hospital Mortality of Physical Trauma Patients Using Artificial Intelligence Techniques: Nationwide Population-Based Study in Korea

Authors of this article:

Seungseok Lee1 Author Orcid Image ;   Wu Seong Kang2 Author Orcid Image ;   Sanghyun Seo3 Author Orcid Image ;   Do Wan Kim4 Author Orcid Image ;   Hoon Ko1 Author Orcid Image ;   Joongsuck Kim2 Author Orcid Image ;   Seonghwa Lee5 Author Orcid Image ;   Jinseok Lee1 Author Orcid Image
Article Authors Cited by (3) Tweetations (4) Metrics

Seungseok Lee   1 * , BE ;   Wu Seong Kang   2 * , MD, PhD ;   Sanghyun Seo   3 * , MD ;   Do Wan Kim   4 * , MD ;   Hoon Ko   1 , MSc ;   Joongsuck Kim   2 , MD ;   Seonghwa Lee   5 , MD, PhD ;   Jinseok Lee   1 , PhD

1 Department of Biomedical Engineering, Kyung Hee University, Yong-in, Republic of Korea

2 Department of Trauma Surgery, Jeju Regional Trauma Center, Cheju Halla General Hospital, Jeju, Republic of Korea

3 Department of Radiology, Wonkwang University Hospital, Iksan, Republic of Korea

4 Department of Thoracic and Cardiovascular Surgery, Chonnam National University Hospital, Chonnam National University Medical School, Gwangju, Republic of Korea

5 Department of Emergency Medicine, Jeju Regional Trauma Center, Cheju Halla General Hospital, Jeju, Republic of Korea

*these authors contributed equally

Corresponding Author:

  • Jinseok Lee, PhD
  • Department of Biomedical Engineering
  • Kyung Hee University
  • 1732, Deogyeong-daero, Giheung-gu
  • Yong-in, 17104
  • Republic of Korea
  • Phone: 82 312012570
  • Fax: 82 312012571
  • Email: gonasago@khu.ac.kr