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

Emerging Technologies for Rehabilitation (364) Generative Language Models Including ChatGPT (753) Occupational Health and Ergonomics/Prevention at the Workplace (317) Tools, Programs and Algorithms (393) New Methods (1151)

Published on in Vol 13 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/80607, first published .
Leveraging Large Language Models for Early Detection of Anomaly Work Injury Cases: Data-Driven Approach to Rehabilitation Efficiency

Leveraging Large Language Models for Early Detection of Anomaly Work Injury Cases: Data-Driven Approach to Rehabilitation Efficiency

Leveraging Large Language Models for Early Detection of Anomaly Work Injury Cases: Data-Driven Approach to Rehabilitation Efficiency

Authors of this article:

Peter Q Chen1 Author Orcid Image ;   Hayley Y W Gu1 Author Orcid Image ;   Heidi K Y Lo2 Author Orcid Image ;   Wing Chung Chang2 Author Orcid Image ;   Cameron J M Lai3 ;   Sun H S Lai3 ;   Andy S K Cheng4 Author Orcid Image ;   Peter H F Ng1 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Peter Q Chen   1 , MSc ;   Hayley Y W Gu   1 , MSc ;   Heidi K Y Lo   2 , MBChB, MRCPsych ;   Wing Chung Chang   2 , MBChB, MD ;   Cameron J M Lai   3 , MBA ;   Sun H S Lai   3 , BSc, PhD ;   Andy S K Cheng   4 , BSc, PhD ;   Peter H F Ng   1 , MSc, PhD

1 Department of Computing, Hong Kong Polytechnic University, Hong Kong, China (Hong Kong)

2 Department of Psychiatry, University of Hong Kong, Hong Kong, China (Hong Kong)

3 Total Rehabilitation Management (HK) Limited, Hong Kong, China (Hong Kong)

4 Department of Health and Physical Education, The Education University of Hong Kong, Hong Kong, China (Hong Kong)

Corresponding Author:

  • Peter H F Ng, MSc, PhD
  • Department of Computing
  • Hong Kong Polytechnic University
  • PQ710, Mong Man Wai Building
  • Hong Kong
  • China (Hong Kong)
  • Phone: 852 27667248
  • Email: peter.nhf@polyu.edu.hk