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

Digital Health Reviews (1724) Artificial Intelligence (2129) Generative Language Models Including ChatGPT (708) AI Language Models in Health Care (202) Natural Language Processing (917) Artificial Intelligence, Machine Learning, and Natural Language Processing for Public Health (87) Theme Issue: ChatGPT and Generative Language Models in Medical Education (115)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/60501, first published .
Prompt Engineering Paradigms for Medical Applications: Scoping Review

Prompt Engineering Paradigms for Medical Applications: Scoping Review

Prompt Engineering Paradigms for Medical Applications: Scoping Review

Authors of this article:

Jamil Zaghir1, 2 Author Orcid Image ;   Marco Naguib3 Author Orcid Image ;   Mina Bjelogrlic1, 2 Author Orcid Image ;   Aurélie Névéol3 Author Orcid Image ;   Xavier Tannier4 Author Orcid Image ;   Christian Lovis1, 2 Author Orcid Image
Article Authors Cited by (48) Tweetations (2) Metrics Author Video

Journals

  1. Zaghir J, Bjelogrlic M, Goldman J, Ehrsam J, Gaudet-Blavignac C, Lovis C, Hassani H. Human-machine interactions with clinical phrase prediction system, aligning with Zipf’s least effort principle?. PLOS ONE 2024;19(12):e0316177 View
  2. Yuan H. Natural Language Processing for Chest X‐Ray Reports in the Transformer Era: BERT‐Like Encoders for Comprehension and GPT‐Like Decoders for Generation. iRADIOLOGY 2025;3(4):295 View
  3. Azimi I, Qi M, Wang L, Rahmani A, Li Y. Evaluation of LLMs accuracy and consistency in the registered dietitian exam through prompt engineering and knowledge retrieval. Scientific Reports 2025;15(1) View
  4. Turner J. Intuitive Human–Artificial Intelligence Theranostic Complementarity. Cancer Biotherapy and Radiopharmaceuticals 2025;40(3):153 View
  5. Monzon N, Hays F. Leveraging Generative Artificial Intelligence to Improve Motivation and Retrieval in Higher Education Learners. JMIR Medical Education 2025;11:e59210 View
  6. Colangelo M, Guizzardi S, Meleti M, Calciolari E, Galli C. How to Write Effective Prompts for Screening Biomedical Literature Using Large Language Models. BioMedInformatics 2025;5(1):15 View
  7. Hao J, Chen Z, Peng Q, Zhao L, Zhao W, Cong S, Li J, Li J, Qian Q, Sun H. Prompt Framework for Extracting Scale-Related Knowledge Entities from Chinese Medical Literature: Development and Evaluation Study. Journal of Medical Internet Research 2025;27:e67033 View
  8. Tung C, Liang S, Chang S, Young C. A Hybrid Artificial Intelligence System for Automated EEG Background Analysis and Report Generation. IEEE Journal of Biomedical and Health Informatics 2025;29(4):2629 View
  9. Qiu Q, Ma Y, Han P, Ma K, Huang Z, Tian M, Wu Q. Domain knowledge-guided geological named entities recognition of rock minerals based on prompt engineering with error feedback mechanism. Computers & Geosciences 2025;201:105944 View
  10. Vorensky M, Peredo D, Ferraro R, Paris E, Mohammadi A, Spano P, Rao S. Improving ChatGPT’s Performance in Orthopedics: Opportunities Using the CRISPE Framework. JOSPT Methods 2025;1(2):56 View
  11. Galli C, Gavrilova A, Calciolari E. Large Language Models in Systematic Review Screening: Opportunities, Challenges, and Methodological Considerations. Information 2025;16(5):378 View
  12. Shreibati J. Prompting Introspection. Circulation 2025;151(19):1375 View
  13. Abrantes J. Assessing Large Language Models for Medical Question Answering in Portuguese: Open-Source Versus Closed-Source Approaches. Cureus 2025 View
  14. Wang K, Lin L, Zheng R, Nan S, Lu X, Duan H. Leveraging large language models for preoperative prevention of cardiopulmonary bypass-associated acute kidney injury. Renal Failure 2025;47(1) View
  15. Zheng Y, Bensahla A, Bjelogrlic M, Zaghir J, Turbe H, Bednarczyk L, Gaudet-Blavignac C, Ehrsam J, Marchand-Maillet S, Lovis C. A scoping review of self-supervised representation learning for clinical decision making using EHR categorical data. npj Digital Medicine 2025;8(1) View
  16. Chen H, Alfred M, Cohen E. Efficient Detection of Stigmatizing Language in Electronic Health Records via In-Context Learning: Comparative Analysis and Validation Study. JMIR Medical Informatics 2025;13:e68955 View
  17. Angyal V, Bertalan Á, Domján P, Dinya E. Exploring the possibilities and limitations of customized large language model to support and improve cervical cancer screening. BMC Medical Informatics and Decision Making 2025;25(1) View
  18. Garin D, Cook S, Ferry C, Bennar W, Togni M, Meier P, Wenaweser P, Puricel S, Arroyo D. Improving large language models accuracy for aortic stenosis treatment via Heart Team simulation: a prompt design analysis. European Heart Journal - Digital Health 2025;6(4):665 View
  19. Kantor J. Generative Artificial Intelligence in Dermatology. Dermatologic Clinics 2025;43(4):603 View
  20. Fang S, Holgate B, Shek A, Winston J, McWilliam M, Viana P, Teo J, Richardson M. Extracting epilepsy‐related information from unstructured clinic letters using large language models. Epilepsia 2025;66(9):3369 View
  21. Lindholz M, Burdenski A, Ruppel R, Schulze-Weddige S, Baumgärtner G, Schobert I, Haack A, Eminovic S, Milnik A, Hamm C, Frisch A, Penzkofer T. Comparing large language models and text embedding models for automated classification of textual, semantic, and critical changes in radiology reports. European Journal of Radiology 2025;191:112316 View
  22. Lee J, Li V, Wu J, Chen H, Su S, Chang B, Lai R, Liu C, Chen C, Tanapima V, Shen T, Atun R. Evaluation of performance of generative large language models for stroke care. npj Digital Medicine 2025;8(1) View
  23. Moëll B, Sand Aronsson F. Harm Reduction Strategies for Thoughtful Use of Large Language Models in the Medical Domain: Perspectives for Patients and Clinicians. Journal of Medical Internet Research 2025;27:e75849 View
  24. Liu J, Liu F, Wang C, Liu S. Prompt Engineering in Clinical Practice: Tutorial for Clinicians. Journal of Medical Internet Research 2025;27:e72644 View
  25. Wang T, Chen R, Wang B, Zou C, Fan N, Yuan S, Wang A, Xi Y, Zang L. Evaluating the Performance of State-of-the-Art Artificial Intelligence Chatbots Based on the WHO Global Guidelines for the Prevention of Surgical Site Infection: Cross-Sectional Study. Journal of Medical Internet Research 2025;27:e75567 View
  26. Ma Y, Zheng S, Yang Z, Zheng P, Leng J, Hong J. Leveraging large language models in next generation intelligent manufacturing: Retrospect and prospect. Journal of Manufacturing Systems 2025;82:809 View
  27. Luo Y, Hooshangnejad H, Feng X, Huang G, Chen X, Zhang R, Chen Q, Ngwa W, Ding K. A Language Vision Model Approach for Automated Tumor Contouring in Radiation Oncology. Bioengineering 2025;12(8):835 View
  28. Bahng J. The Potential and Applications of Artificial Intelligence in the Field of Audiology. Audiology and Speech Research 2025;21(3):209 View
  29. Takahashi G, von Liechti L, Tarshizi E. Quo Vadis, AI-Empowered Doctor?. JMIR Medical Education 2025;11:e70079 View
  30. Hasnain M, Aurangzeb K, Alhussein M, Ghani I, Mahmood M. AI in conjunctivitis research: assessing ChatGPT and DeepSeek for etiology, intervention, and citation integrity via hallucination rate analysis. Frontiers in Artificial Intelligence 2025;8 View
  31. Syahputri I, Budiardjo E, Putra P. Unlocking the Potential of the Prompt Engineering Paradigm in Software Engineering: A Systematic Literature Review. AI 2025;6(9):206 View
  32. Nuttah M, Algabroun H, Linhares C, Håkansson L. Creative Destruction and Technological Paradigms in Manufacturing: A Large-Scale Review and Framework for Technology Portfolio Assessment. IEEE Transactions on Engineering Management 2025;72:3397 View
  33. Alter I, Chan K, Andreadis K, Rameau A. Generative Artificial Intelligence Methodology Reporting in Otolaryngology: A Scoping Review. The Laryngoscope 2025 View
  34. Çolpak E, Yılmaz D. Benchmarking Different Natural Language Processing Models for Their Responses to Queries on Toothsupported Fixed Dental Prostheses in Terms of Accuracy and Consistency. ADO Klinik Bilimler Dergisi 2025;14(3):215 View
  35. Esmaeilzadeh P. Ethical implications of using general-purpose LLMs in clinical settings: a comparative analysis of prompt engineering strategies and their impact on patient safety. BMC Medical Informatics and Decision Making 2025;25(1) View
  36. van Breugel M, Greenhawt M, Eguiluz-Gracia I, Torres Jaén M, Anagnostou A, Koppelman G. Artificial intelligence in allergy and immunology: Recent developments, implementation challenges, and the road toward clinical impact. Journal of Allergy and Clinical Immunology 2025 View
  37. Ben-Zeev D. To AI, or Not to AI: That Is Not the Question. Psychiatric Services 2025 View
  38. Shawi R, Jamel L. Leveraging ChatGPT and explainable AI for enhancing clinical decision support. Scientific Reports 2025;15(1) View
  39. Berghea F, Berghea E, Daia C, Ciuc D, Dinca G. In the search for the perfect prompt in medical AI queries. Frontiers in Artificial Intelligence 2025;8 View
  40. Peng W, Meng J, Tang L, Zou W, Issaka B. How Do Lay Users Seek Information with ChatGPT: An In-Situ Interview Study. International Journal of Human–Computer Interaction 2025:1 View
  41. Xu Y, Jia H, Wang M, Feng J, Xu X, Wang H, Chen J, Zheng Z, Yang X, Shen Y, Wang J, Zhuang C, Wei P, Guo R, Zhao X, Fan J, Sun X. Enhancing clinical documentation with voice processing and large language models: a study on the LAOS system. npj Digital Medicine 2025 View

Books/Policy Documents

  1. Bolpagni M, De Carli S, Sanna L, Gabrielli S, Dragoni M. Artificial Intelligence in Medicine. View
  2. Tang J, Abedi A, Colella T, Khan S. ArtifiAI for Aging Rehabilitation and Intelligent Assisted Living. View
  3. Hirosawa T. Artificial Intelligence in Medical Diagnostics. View
  4. Hirosawa T. Artificial Intelligence in Medical Diagnostics. View

Conference Proceedings

  1. Castagnari E, Muyama L, Coulet A. 2024 2nd International Conference on Foundation and Large Language Models (FLLM). Prompting Large Language Models for Supporting the Differential Diagnosis of Anemia View
  2. Mondal C, Pham D, Gupta A, Tan T, Gedeon T. Companion Proceedings of the ACM on Web Conference 2025. Leveraging Prompt Engineering with Lightweight Large Language Models to Label and Extract Clinical Information from Radiology Reports View
  3. Koleilat T, Asgariandehkordi H, Rivaz H, Xiao Y. 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). BiomedCoOp: Learning to Prompt for Biomedical Vision-Language Models View