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

Depression and Mood Disorders; Suicide Prevention (2517) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (2714) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (3336) Natural Language Processing (1326) Artificial Intelligence (4956) Generative Language Models Including ChatGPT (1611)

Published on in Vol 13 (2026)

This is a member publication of Bibsam Consortium

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/98925, first published .
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Ensemble of Domain-Specific Natural Language Processing and Large Language Models for Detecting Suicidal Ideation and Mental Health Conditions in Social Media Text: Development and Evaluation Study

Ensemble of Domain-Specific Natural Language Processing and Large Language Models for Detecting Suicidal Ideation and Mental Health Conditions in Social Media Text: Development and Evaluation Study

Authors of this article:

Thomas Kallstenius1 Author Orcid Image ;   Basil Duvernoy2 Author Orcid Image ;   Adam Kallstenius1 Author Orcid Image ;   Andrea Johansson Capusan2 Author Orcid Image ;   Adam Williamson2, 3 Author Orcid Image
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Thomas Kallstenius   1 , PhD ;   Basil Duvernoy   2 , PhD ;   Adam Kallstenius   1 ;   Andrea Johansson Capusan   2 , MD, PhD ;   Adam Williamson   2, 3 , PhD

1 NeuroPrism AB, Norrköping, Sweden

2 Center for Social and Affective Neuroscience, Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Östergötland, Sweden

3 International Clinical Research Center, St. Anne’s University Hospital Brno, Brno, Czech Republic

Corresponding Author:

  • Adam Williamson, PhD
  • Center for Social and Affective Neuroscience
  • Department of Biomedical and Clinical Sciences
  • Linköping University
  • SE-581 83
  • Linköping, Östergötland
  • Sweden
  • Phone: 46 0782188942
  • Email: adam.williamson@liu.se