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

Infoveillance and Social Listening (438) Infodemiology and Infoveillance (2042) Natural Language Processing (1329) Opioid and Related Substance Misuse (243) AI Applications in Public Health (114)

Published on in Vol 6 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/77783, first published .
Doctors analyze medical data on screens showing risk levels and brain scans.

Automated Risk Assessment of Opioid Use: Analysis Using Pre-Trained Transformers on Social Media Data

Automated Risk Assessment of Opioid Use: Analysis Using Pre-Trained Transformers on Social Media Data

Authors of this article:

Muhammad Ahmad1 Author Orcid Image ;   Rita Orji2 Author Orcid Image ;   Maaz Amjad3 Author Orcid Image ;   Abubakar Siddique4 Author Orcid Image ;   Nailya Kubysheva5 Author Orcid Image ;   Ildar Batyrshin1 Author Orcid Image ;   Grigori Sidorov1 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Ahmad M, Orji R, Ullah F, Batyrshin I, Sidorov G. Detecting Opioid Misuse on Social Media via Named Entity Recognition (NER) With Deep Learning. Expert Systems 2026;43(8) View
  2. Ahmad M, Siddique A, Orji R, Olatinwo S, Sidorov G. Multilingual Emotion Detection in Social Media Using an Attention-Enhanced and Explainable Machine Learning Framework. IEEE Transactions on Computational Social Systems 2026;13(5):5817 View