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

There are no citations yet available for this article according to Crossref .