Generative Language Models Including ChatGPT
Articles published in 2026 in this theme: 331 (scroll down to load remaining articles)
2026
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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Tool or Companion? Reframing Conversational AI to Prevent Psychological Harm
JMIR Ment Health 2026 (Sep 10); 13:e99354
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AI-Assisted Angoff Standard Setting for Multiple-Choice Examinations in Medical Education: Comparative Study
JMIR Med Educ 2026 (Sep 09); 12:e98766
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“Small” Large Language Models in the Hospital: Evaluation Study on Real-World Data in a Resource-Constrained Setting
J Med Internet Res 2026 (Sep 09); 28:e86453
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Closing the Solidarity Gap Requires Closing the Accountability Gap for Patient-Facing AI
J Med Internet Res 2026 (Sep 08); 28:e108685
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Sentence-Level Provenance for AI Medical Record Summarization in a Click-to-Inspect Interface: Formative Usability Evaluation
JMIR Hum Factors 2026 (Sep 08); 13:e95644
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Large Language Models for Heterogeneous Data Mining in Liver Disease: Framework Development and Retrospective Validation Study
J Med Internet Res 2026 (Sep 04); 28:e92921
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Scaffolded AI-Supported Problem-Based Learning for Medical Interns: Exploratory Retrospectively Registered Randomized Controlled Evaluation With a Voluntary Feasibility Follow-Up
JMIR Med Educ 2026 (Sep 03); 12:e95039
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A Secure, Scalable Large Language Model–Based System (CIDER) for High-Throughput Clinical Data Extraction From Medical Reports: Retrospective Validation Study
J Med Internet Res 2026 (Sep 02); 28:e95780
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