Generative Language Models Including ChatGPT
Articles published in 2026 in this theme: 339 (scroll down to load remaining articles)
2026
Demographics, Clinical Content, Use Patterns, and Care-Seeking Intent Across Two Generations of AI-Enabled Clinical Triage Tools (A Traditional Structured Questionnaire and a Large Language Model–Enabled Conversational Interface): Comparative Retrospective Observational Study
JMIR AI 2026 (Sep 22); 5:e84469
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Generative AI–Assisted Progressive-Disclosure Case-Based Learning for Clinical Reasoning in Occupational Medicine: Quasi-Experimental Study
JMIR Med Educ 2026 (Sep 22); 12:e103584
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Large Language Model Performance on Multistep Clinical Cases: Comparative Study Across Question and Case Levels
JMIR Med Educ 2026 (Sep 22); 12:e95342
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Process-Oriented, Behaviorally Anchored Assessment of Clinical Reasoning in Large Language Models and the Effect of Extended Thinking: Protocol for a Prospective, Multigroup, Comparative Study
JMIR Res Protoc 2026 (Sep 22); 15:e103220
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Large Language Models for Clinical Data Extraction in Workplace Injury Rehabilitation: Protocol for a Retrospective Pilot Study of Accuracy, Fairness, and Methodological Considerations in Workers’ Compensation Medical Chart Review
JMIR Res Protoc 2026 (Sep 22); 15:e99807
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Real-Time Artificial Intelligence Diagnostic Copilot in Simulated Primary Care Consultations: Randomized Simulation Study
JMIR Form Res 2026 (Sep 22); 10:e104579
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A Clinician-Centered Evaluation Framework for Large Language Models in Patient Education: Integrating the Technology Acceptance Model and Medical Condition Regard Scale
JMIR Form Res 2026 (Sep 21); 10:e100423
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The Alignment Paradox of Medical Large Language Models in Infertility Care: Decoupling Algorithmic Improvement From Clinical Decision-Making Quality
J Med Internet Res 2026 (Sep 21); 28:e97221
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Hospital Human Resource Managers’ Perspectives on Organizational Readiness for Generative AI Skills: Qualitative Descriptive Study
JMIR Med Inform 2026 (Sep 17); 14:e74339
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The AWARE (AI Use, Why, Attachment, Reality and Risk, and Effect on Functioning) Framework for Assessing Patients’ Use of AI in Mental Health Care
JMIR Med Educ 2026 (Sep 16); 12:e108766
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Problematic Reliance on Generative AI in an Anxious Young Adult: Case Report
JMIR Form Res 2026 (Sep 16); 10:e98297
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Psychological Therapy in the Age of Large Language Models: Framework for Therapist-Delivered and AI-Supported Functions
JMIR Ment Health 2026 (Sep 16); 13:e103712
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Attitudes Toward Large Language Models in Health Care and Preferences for Their Adoption and Oversight Among Health Care Professionals: Cross-Sectional Survey
J Med Internet Res 2026 (Sep 15); 28:e87818
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Frameworks, Methodologies, and Tools for Evaluating Large Language Models in Digital Mental Health Interventions: Protocol for a Scoping Review
JMIR Res Protoc 2026 (Sep 14); 15:e91677
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Adaptive Optics Image Analysis Using Generative AI (GPT-4) Scripting: Exploratory Study
JMIR Form Res 2026 (Sep 14); 10:e94906
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Privacy Leakage in Federated Learning in Radiology Reports: Comparative Evaluation of Tokenizer and Batch-Size Privacy Risks
JMIR Med Inform 2026 (Sep 11); 14:e88390
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Evaluating Large Language Models in Clinical Audiology (AUDIOLOGYBENCH): Benchmark Development and Validation Study
J Med Internet Res 2026 (Sep 11); 28:e94755
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Performance of Cloud-Hosted Large Vision-Language Models on the Japanese National Examination for Clinical Laboratory Technicians: Comparative Benchmarking Study
JMIR Med Educ 2026 (Sep 11); 12:e84266
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Generative AI Use, Perceived Usefulness, Perceived Risk, and Physician Burnout and Fulfillment Among Chinese Physicians: Mixed Methods Multiregional Study
J Med Internet Res 2026 (Sep 11); 28:e94155
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Exploring Bias in Medical Applications of Large Language Models: Protocol for a Systematic Review
JMIR Res Protoc 2026 (Sep 10); 15:e91348
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