Published on in Vol 9, No 1 (2021): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/24973, first published .
Deep Learning Models for Predicting Severe Progression in COVID-19-Infected Patients: Retrospective Study

Deep Learning Models for Predicting Severe Progression in COVID-19-Infected Patients: Retrospective Study

Deep Learning Models for Predicting Severe Progression in COVID-19-Infected Patients: Retrospective Study

Thao Thi Ho   1 * , MS ;   Jongmin Park   2 * , MD ;   Taewoo Kim   1 , BS ;   Byunggeon Park   2 , MD ;   Jaehee Lee   3 , MD, PhD ;   Jin Young Kim   4 , MD ;   Ki Beom Kim   5 , MD ;   Sooyoung Choi   6 , MD ;   Young Hwan Kim   7 , MD ;   Jae-Kwang Lim   2 , MD ;   Sanghun Choi   1 , PhD

1 School of Mechanical Engineering, Kyungpook National University, Daegu, Republic of Korea

2 Department of Radiology, School of Medicine, Kyungpook National University, Daegu, Republic of Korea

3 Department of Internal Medicine, School of Medicine, Kyungpook National University, Daegu, Republic of Korea

4 Department of Radiology, Keimyung University Dongsan Hospital, Daegu, Republic of Korea

5 Department of Radiology, Daegu Fatima Hospital, Daegu, Republic of Korea

6 Department of Radiology, Yeungnam University Medical Center, Daegu, Republic of Korea

7 Department of Radiology, School of Medicine, Daegu Catholic University, Daegu, Republic of Korea

*these authors contributed equally

Corresponding Author:

  • Sanghun Choi, PhD
  • School of Mechanical Engineering
  • Kyungpook National University
  • 80 Daehak-ro, Buk-gu
  • Daegu, 41566
  • Republic of Korea
  • Phone: 82 53-950-5578
  • Fax: 82 53-950-6550
  • Email: s-choi@knu.ac.kr