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

AI in Older Adult Care (45) Generative Language Models Including ChatGPT (789) Chatbots and Conversational Agents (778) AI Language Models in Health Care (237) Artificial Intelligence (2314) Adverse Drug Events Detection, Pharmacovigilance and Surveillance (225) Natural Language Processing (945)

Published on in Vol 8 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/69504, first published .
Identifying Deprescribing Opportunities With Large Language Models in Older Adults: Retrospective Cohort Study

Identifying Deprescribing Opportunities With Large Language Models in Older Adults: Retrospective Cohort Study

Identifying Deprescribing Opportunities With Large Language Models in Older Adults: Retrospective Cohort Study

Authors of this article:

Vimig Socrates1, 2 Author Orcid Image ;   Donald S Wright3, 4 Author Orcid Image ;   Thomas Huang3 Author Orcid Image ;   Soraya Fereydooni3 Author Orcid Image ;   Christine Dien2 Author Orcid Image ;   Ling Chi3 Author Orcid Image ;   Jesse Albano5 Author Orcid Image ;   Brian Patterson6 Author Orcid Image ;   Naga Sasidhar Kanaparthy3, 4 Author Orcid Image ;   Catherine X Wright7 Author Orcid Image ;   Andrew Loza1, 3 Author Orcid Image ;   David Chartash1, 8 Author Orcid Image ;   Mark Iscoe1, 3 Author Orcid Image ;   Richard Andrew Taylor1, 3, 9 Author Orcid Image
Article Authors Cited by (4) Tweetations Metrics

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  2. Al Meslamani A, Abou Hajal A. Language models for drug–drug interactions: current applications, pitfalls, and future directions. Expert Opinion on Drug Metabolism & Toxicology 2025;21(9):1083 View
  3. Misra S, Das R, Mohapatra S, Dey A. Knowledge, attitude, and practice of dentists in India regarding geriatric oral healthcare and polypharmacy management: a cross-sectional study. BMC Geriatrics 2026 View
  4. Fine Smilovich E, Kalsy M, Wozneak K, Syed Q, Solberg L. Leveraging AI to Advance Age-Friendly Care in the Veterans Health Administration. JMIR Aging 2026;9:e75686 View