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

Development and Evaluation of Research Methods, Instruments and Tools (744) Natural Language Processing (917) Research Methodology - AI (36) Applications of AI (285) Adverse Drug Events Detection, Pharmacovigilance and Surveillance (215) Machine Learning (2074) Clinical Informatics (1325) Electronic Health Records (1319)

Published on in Vol 9 (2025)

This is a member publication of Bibsam Consortium

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/71949, first published .
Identifying Adverse Drug Events in Clinical Text Using Fine-Tuned Clinical Language Models: Machine Learning Study

Identifying Adverse Drug Events in Clinical Text Using Fine-Tuned Clinical Language Models: Machine Learning Study

Identifying Adverse Drug Events in Clinical Text Using Fine-Tuned Clinical Language Models: Machine Learning Study

Authors of this article:

Elizaveta Kopacheva1 Author Orcid Image ;   Aron Henriksson2 Author Orcid Image ;   Hercules Dalianis2 Author Orcid Image ;   Tora Hammar3 Author Orcid Image ;   Alisa Lincke1 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Elizaveta Kopacheva   1 , PhD ;   Aron Henriksson   2 , Prof Dr ;   Hercules Dalianis   2 , Prof Dr ;   Tora Hammar   3 , Prof Dr ;   Alisa Lincke   1 , PhD

1 Department of Computer Science and Media Technology, Faculty of Technology, Linnaeus University, Växjö, Sweden

2 Department of Computer and Systems Sceince, Stockholm University, Kista, Sweden

3 eHealth Institute, Department of Medicine and Optometry, Faculty of Health and Life Sciences, Linnaeus University, Växjö, Sweden

Corresponding Author:

  • Elizaveta Kopacheva, PhD
  • Department of Computer Science and Media Technology
  • Faculty of Technology, Linnaeus University
  • Universitetsplatsen 1
  • Växjö 352 52
  • Sweden
  • Phone: 46 737033730
  • Email: elizaveta.kopacheva@lnu.se