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

Theme Issue: Medical Informatics and COVID-19 (107) JMIR Theme Issue: COVID-19 Special Issue (2461) Clinical Information and Decision Making (1434) Theme Issue: Novel Coronavirus (COVID-19) Outbreak Rapid Reports (1520) Outbreak and Pandemic Preparedness and Management (1743) Infectious Diseases (non-STD/STI) (1592) Decision Support for Health Professionals (1210) Artificial Intelligence (1421) Machine Learning (1501)

Published on in Vol 9, No 11 (2021): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/32726, first published .
Optimal Triage for COVID-19 Patients Under Limited Health Care Resources With a Parsimonious Machine Learning Prediction Model and Threshold Optimization Using Discrete-Event Simulation: Development Study

Optimal Triage for COVID-19 Patients Under Limited Health Care Resources With a Parsimonious Machine Learning Prediction Model and Threshold Optimization Using Discrete-Event Simulation: Development Study

Optimal Triage for COVID-19 Patients Under Limited Health Care Resources With a Parsimonious Machine Learning Prediction Model and Threshold Optimization Using Discrete-Event Simulation: Development Study

Authors of this article:

Jeongmin Kim1 Author Orcid Image ;   Hakyung Lim1 Author Orcid Image ;   Jae-Hyeon Ahn1 Author Orcid Image ;   Kyoung Hwa Lee2 Author Orcid Image ;   Kwang Suk Lee3 Author Orcid Image ;   Kyo Chul Koo3 Author Orcid Image
Article Authors Cited by (10) Tweetations (3) Metrics

Jeongmin Kim   1 * , BBA ;   Hakyung Lim   1 * , MSc ;   Jae-Hyeon Ahn   1 , PhD ;   Kyoung Hwa Lee   2 , MD, MMS ;   Kwang Suk Lee   3 * , MD, MMS ;   Kyo Chul Koo   3 * , MD, PhD

1 College of Business, Korea Advanced Institute of Science and Technology, Seoul, Republic of Korea

2 Division of Infectious Disease, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea

3 Department of Urology, Yonsei University College of Medicine, Seoul, Republic of Korea

*these authors contributed equally

Corresponding Author:

  • Kyo Chul Koo, MD, PhD
  • Department of Urology
  • Yonsei University College of Medicine
  • 211 Eonju-ro, Gangnam-gu
  • Seoul, 135-720
  • Republic of Korea
  • Phone: 82 01099480342
  • Fax: 82 0234628887
  • Email: gckoo@yuhs.ac