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

Theme Issue: ChatGPT and Generative Language Models in Medical Education (94) Chatbots and Conversational Agents (604) Generative Language Models Including ChatGPT (447) Clinical Information and Decision Making (1581) Decision Support for Health Professionals (1308) Machine Learning (1660) Artificial Intelligence (1638)

Published on in Vol 10 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/51391, first published .
Learning to Make Rare and Complex Diagnoses With Generative AI Assistance: Qualitative Study of Popular Large Language Models

Learning to Make Rare and Complex Diagnoses With Generative AI Assistance: Qualitative Study of Popular Large Language Models

Learning to Make Rare and Complex Diagnoses With Generative AI Assistance: Qualitative Study of Popular Large Language Models

Authors of this article:

Tassallah Abdullahi1 Author Orcid Image ;   Ritambhara Singh1, 2 Author Orcid Image ;   Carsten Eickhoff3 Author Orcid Image
Article Authors Cited by (20) Tweetations (5) Metrics

Journals

  1. Cheng J. Applications of Large Language Models in Pathology. Bioengineering 2024;11(4):342 View
  2. Bragazzi N, Garbarino S. Toward Clinical Generative AI: Conceptual Framework. JMIR AI 2024;3:e55957 View
  3. Abdullahi T, Mercurio L, Singh R, Eickhoff C. Retrieval-Based Diagnostic Decision Support: Mixed Methods Study. JMIR Medical Informatics 2024;12:e50209 View
  4. Oami T, Okada Y, Nakada T. Performance of a Large Language Model in Screening Citations. JAMA Network Open 2024;7(7):e2420496 View
  5. Fabijan A, Zawadzka-Fabijan A, Fabijan R, Zakrzewski K, Nowosławska E, Polis B. Assessing the Accuracy of Artificial Intelligence Models in Scoliosis Classification and Suggested Therapeutic Approaches. Journal of Clinical Medicine 2024;13(14):4013 View
  6. Huang T, Safranek C, Socrates V, Chartash D, Wright D, Dilip M, Sangal R, Taylor R. Patient-Representing Population's Perceptions of GPT-Generated Versus Standard Emergency Department Discharge Instructions: Randomized Blind Survey Assessment. Journal of Medical Internet Research 2024;26:e60336 View
  7. Scott I, Miller T, Crock C. Using conversant artificial intelligence to improve diagnostic reasoning: ready for prime time?. Medical Journal of Australia 2024;221(5):240 View
  8. Kaczmarczyk R, Wilhelm T, Martin R, Roos J. Evaluating multimodal AI in medical diagnostics. npj Digital Medicine 2024;7(1) View
  9. Montalvo F, Pavlov K, Thai P, Devkota B, Takahashi B. Machine Learning and Human Expertise in the Balance: Generative AI in Healthcare Settings. Proceedings of the International Symposium on Human Factors and Ergonomics in Health Care 2024;13(1):211 View
  10. De Araújo Neto A, Pinto G, Corrêa J, Soares L, Batista C, Pinheiro F, Teles A. Chatbots na identificação de problemas de amamentação: avaliação de desempenho. Journal of Health Informatics 2024;16(Especial) View
  11. Ho C, Tian T, Ayers A, Aaron R, Phillips V, Wolf R, Mathioudakis N, Dai T, Klonoff D. Qualitative metrics from the biomedical literature for evaluating large language models in clinical decision-making: a narrative review. BMC Medical Informatics and Decision Making 2024;24(1) View
  12. Biesheuvel L, Workum J, Reuland M, van Genderen M, Thoral P, Dongelmans D, Elbers P. Large language models in critical care. Journal of Intensive Medicine 2025;5(2):113 View
  13. Yamamura Y, Fujii K, Nakashima C, Otsuka A. Evaluation of the Accuracy of Artificial Intelligence (AI) Models in Dermatological Diagnosis and Comparison With Dermatology Specialists. Cureus 2025 View
  14. Nan D, Zhao X, Chen C, Sun S, Lee K, Kim J. Bibliometric Analysis on ChatGPT Research with CiteSpace. Information 2025;16(1):38 View
  15. Gao Y, Myers S, Chen S, Dligach D, Miller T, Bitterman D, Chen G, Mayampurath A, Churpek M, Afshar M. Uncertainty estimation in diagnosis generation from large language models: next-word probability is not pre-test probability. JAMIA Open 2024;8(1) View
  16. Wu C, Liu W, Mei P, Liu Y, Cai J, Liu L, Wang J, Ling X, Wang M, Cheng Y, He M, He Q, He Q, Yuan X, Tong J. The large language model diagnoses tuberculous pleural effusion in pleural effusion patients through clinical feature landscapes. Respiratory Research 2025;26(1) View
  17. Takita H, Kabata D, Walston S, Tatekawa H, Saito K, Tsujimoto Y, Miki Y, Ueda D. A systematic review and meta-analysis of diagnostic performance comparison between generative AI and physicians. npj Digital Medicine 2025;8(1) View
  18. Merdler-Rabinowicz R, Omar M, Ganesh J, Morava E, Nadkarni G, Klang E. The role of large language models in medical genetics. Molecular Genetics and Metabolism 2025;145(1):109098 View

Books/Policy Documents

  1. Musunuri R, Bhatt A. Improving Healthcare Quality and Patient Engagement. View