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

Altmetric

Altmetric discovers Social Media mentions. Click the ‘See more details’ link for a full report.

Dimensions

Dimensions discovers Citations. Click the ‘details’ link for a full report.

Metrics Since Publication

Download .csv
Daily | Monthly | Annually