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

Theme Issue: ChatGPT and Generative Language Models in Medical Education (115) Chatbots and Conversational Agents (740) Generative Language Models Including ChatGPT (708) Clinical Information and Decision Making (1915) Decision Support for Health Professionals (1539) Machine Learning (2076) Artificial Intelligence (2129)

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 (39) Tweetations (5) Metrics

Journals

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  2. Bragazzi N, Garbarino S. Toward Clinical Generative AI: Conceptual Framework. JMIR AI 2024;3:e55957 View
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  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
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  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
  19. Sadowsky S. Can ChatGPT be trusted as a resource for a scholarly article on treatment planning implant-supported prostheses?. The Journal of Prosthetic Dentistry 2025;134(2):438 View
  20. Kim H, Kim B, Choi M, Choi J, Oh S, Rha S. Conversion of Mixed-Language Free-Text CT Reports of Pancreatic Cancer to National Comprehensive Cancer Network Structured Reporting Templates by Using GPT-4. Korean Journal of Radiology 2025;26(6):557 View
  21. Kremer P, Schiebisch H, Lechner F, Haase I, Cirkel L, Kötter I, Kuhn S, Krusche M, Knitza J. Comparative analysis of large language models and traditional diagnostic decision support systems for rare rheumatic disease identification. EULAR Rheumatology Open 2025;1(2):51 View
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  23. Oami T, Okada Y, Nakada T. Optimal large language models to screen citations for systematic reviews. Research Synthesis Methods 2025;16(6):859 View
  24. Qian Y. Prompt Engineering in Education: A Systematic Review of Approaches and Educational Applications. Journal of Educational Computing Research 2025;63(7-8):1782 View
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  27. Lin Y, Luo Z, Ye Z, Zhong N, Zhao L, Zhang L, Li X, Chen Z, Chen Y. Applications, Challenges, and Prospects of Generative Artificial Intelligence Empowering Medical Education: Scoping Review. JMIR Medical Education 2025;11:e71125 View
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  29. Yu H, Chen T, Zhang X, Yang Y, Liu Q, Yang C, Shen K, Li H, Tang W, Zhong X, Shuai X, Yu X, Liao Y, Wang C, Zhu H, Wu Y. Performance of Large Language Models in Diagnosing Rare Hematologic Diseases and the Impact of Their Diagnostic Outputs on Physicians: Combined Retrospective and Prospective Study. Journal of Medical Internet Research 2025;27:e77334 View
  30. Li X, Yan X, Lai H, Metwally A. The ethical challenges in the integration of artificial intelligence and large language models in medical education: A scoping review. PLOS One 2025;20(10):e0333411 View
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Books/Policy Documents

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

Conference Proceedings

  1. Berger A, Berghaus D, Bashir A, Grigull L, Fendrich L, Lagones T, Högl H, Ernst G, Schmidt R, Bascom D, Deußer T, Bell T, Lübbering M, Sifa R. 2024 IEEE International Conference on Big Data (BigData). Advancing Personalized Medicine: A Scalable LLM-based Recommender System for Patient Matching View
  2. Abdullahi T, Gemou I, Nayak N, Murtaza G, Bach S, Eickhoff C, Singh R. Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2. K-Paths: Reasoning over Graph Paths for Drug Repurposing and Drug Interaction Prediction View