Published on in Vol 12 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/48862, first published .
Interpretable Deep Learning System for Identifying Critical Patients Through the Prediction of Triage Level, Hospitalization, and Length of Stay: Prospective Study

Interpretable Deep Learning System for Identifying Critical Patients Through the Prediction of Triage Level, Hospitalization, and Length of Stay: Prospective Study

Interpretable Deep Learning System for Identifying Critical Patients Through the Prediction of Triage Level, Hospitalization, and Length of Stay: Prospective Study

Yu-Ting Lin   1 * , MSc ;   Yuan-Xiang Deng   1 * , MSc ;   Chu-Lin Tsai   2 * , MD, SCD ;   Chien-Hua Huang   2 * , MD, PhD ;   Li-Chen Fu   1 * , PhD

1 Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan

2 Department of Emergency Medicine, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan

*all authors contributed equally

Corresponding Author:

  • Li-Chen Fu, PhD
  • Department of Computer Science and Information Engineering
  • National Taiwan University
  • CSIE Der Tian Hall No. 1, Sec. 4, Roosevelt Road
  • Taipei, 106319
  • Taiwan
  • Phone: 886 935545846
  • Email: lichen@ntu.edu.tw