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

Digital Health Reviews (3742) Clinical Information and Decision Making (3798) Decision Support for Health Professionals (2283) Methods and Instruments in Medical Informatics (421) Continuing Medical Education (CME) for Doctors (223) New Methods and Approaches in Medical Education (650)

Published on in Vol 28 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/104092, first published .
Medical professionals review AI-powered medical imaging analysis on multiple computer screens.

Fine-Tuning, Retrieval-Augmented Generation, and Hybrid Adaptation of Language Models for Clinical Decision-Making in Health Care: Systematic Review

Fine-Tuning, Retrieval-Augmented Generation, and Hybrid Adaptation of Language Models for Clinical Decision-Making in Health Care: Systematic Review

Authors of this article:

Anshum Patel1 ;   Yugant Khand2 Author Orcid Image ;   Sai Krishna Vallamchetla2 ;   Pengze Li3 Author Orcid Image ;   Cui Tao3 Author Orcid Image ;   Joseph Cheung1, 3 Author Orcid Image
Article Authors Cited by Tweetations Metrics

Anshum Patel   1 , MD ;   Yugant Khand   2 , MBBS ;   Sai Krishna Vallamchetla   2 , MD ;   Pengze Li   3 , PhD ;   Cui Tao   3 , PhD ;   Joseph Cheung   1, 3 , MD, MS

1 Division of Pulmonary, Allergy and Sleep Medicine, Mayo Clinic, Jacksonville, FL, United States

2 Department of Neurology, Mayo Clinic in Florida, Jacksonville, FL, United States

3 Department of Artificial Intelligence and Informatics, Mayo Clinic in Florida, Jacksonville, FL, United States

Corresponding Author:

  • Joseph Cheung, MD, MS
  • Division of Pulmonary, Allergy and Sleep Medicine
  • Mayo Clinic
  • 4500 San Pablo Road South
  • Jacksonville, FL
  • United States
  • Phone: 1 904-953-2000
  • Email: Cheung.Joseph@mayo.edu