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

Ethical, Legal, and Social Issues in AI (108) Personal Health Records, Patient-Accessible Electronic Health Records, Patient Portals (704) Applications of AI (299) Generative Language Models Including ChatGPT (740) Electronic Health Records (1335)

Published on in Vol 4 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/57828, first published .
Harnessing Moderate-Sized Language Models for Reliable Patient Data Deidentification in Emergency Department Records: Algorithm Development, Validation, and Implementation Study

Harnessing Moderate-Sized Language Models for Reliable Patient Data Deidentification in Emergency Department Records: Algorithm Development, Validation, and Implementation Study

Harnessing Moderate-Sized Language Models for Reliable Patient Data Deidentification in Emergency Department Records: Algorithm Development, Validation, and Implementation Study

Authors of this article:

Océane Dorémus1 Author Orcid Image ;   Dylan Russon1 Author Orcid Image ;   Benjamin Contrand1 Author Orcid Image ;   Ariel Guerra-Adames1, 2 Author Orcid Image ;   Marta Avalos-Fernandez2 Author Orcid Image ;   Cédric Gil-Jardiné1, 3 Author Orcid Image ;   Emmanuel Lagarde1 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Conference Proceedings

  1. Huang C, Lin Y, Chen J, Chao A. 2025 IEEE 14th Global Conference on Consumer Electronics (GCCE). LLM–SLM Hybrid Agents for Secure Audit Processing View
  2. Muthukrishnan H, George J, Aggarwal A. 2025 International Seminar on Application for Technology of Information and Communication (iSemantic). A Policy-Aware Framework for Data Masking: Secure Integration of Applications and Artificial Intelligence in Healthcare and Financial Services View