Machine learning-based prediction of critical illness in children visiting the emergency department.

Journal: PloS one
Published Date:

Abstract

OBJECTIVES: Triage is an essential emergency department (ED) process designed to provide timely management depending on acuity and severity; however, the process may be inconsistent with clinical and hospitalization outcomes. Therefore, studies have attempted to augment this process with machine learning models, showing advantages in predicting critical conditions and hospitalization outcomes. The aim of this study was to utilize nationwide registry data to develop a machine learning-based classification model to predict the clinical course of pediatric ED visits.

Authors

  • Soyun Hwang
    Department of Pediatrics, Severance Children's Hospital, Yonsei University College of Medicine, Seoul, Korea.
  • Bongjin Lee
    Department of Emergency Medicine, Seoul National University Hospital, Seoul, Korea.