Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/50638, first published .
Prompt Engineering as an Important Emerging Skill for Medical Professionals: Tutorial

Prompt Engineering as an Important Emerging Skill for Medical Professionals: Tutorial

Prompt Engineering as an Important Emerging Skill for Medical Professionals: Tutorial

Authors of this article:

Bertalan Meskó 1 Author Orcid Image

Journals

  1. Meskó B. The Impact of Multimodal Large Language Models on Health Care’s Future. Journal of Medical Internet Research 2023;25:e52865 View
  2. Lund B. The prompt engineering librarian. Library Hi Tech News 2023;40(8):6 View
  3. Sallam M, Barakat M, Sallam M. Pilot Testing of a Tool to Standardize the Assessment of the Quality of Health Information Generated by Artificial Intelligence-Based Models. Cureus 2023 View
  4. Shu L, He Q, Yan B, Wu D, Wang M, Wang C, Zhang L. Human‐in‐the‐loop: Human involvement in enhancing medical inquiry performance in large language models. Allergy 2023 View
  5. Sallam M, Al-Salahat K. Below average ChatGPT performance in medical microbiology exam compared to university students. Frontiers in Education 2023;8 View
  6. Sallam M, Al-Salahat K, Al-Ajlouni E. ChatGPT Performance in Diagnostic Clinical Microbiology Laboratory-Oriented Case Scenarios. Cureus 2023 View
  7. Non L. All aboard the ChatGPT steamroller: Top 10 ways to make artificial intelligence work for healthcare professionals. Antimicrobial Stewardship & Healthcare Epidemiology 2023;3(1) View
  8. Patil N, Huang R, Caterine S, Yao J, Larocque N, van der Pol C, Stubbs E. Artificial Intelligence Chatbots’ Understanding of the Risks and Benefits of Computed Tomography and Magnetic Resonance Imaging Scenarios. Canadian Association of Radiologists Journal 2024 View
  9. NYAABA M, ZHAI X. Generative AI Professional Development Needs for Teacher Educators. Journal of AI 2024;8(1):1 View
  10. Sallam M, Barakat M, Sallam M. A Preliminary Checklist (METRICS) to Standardize the Design and Reporting of Studies on Generative Artificial Intelligence–Based Models in Health Care Education and Practice: Development Study Involving a Literature Review. Interactive Journal of Medical Research 2024;13:e54704 View
  11. Mishra V, Sarraju A, Kalwani N, Dexter J. Evaluation of Prompts to Simplify Cardiovascular Disease Information Using a Large Language Model: Cross-Sectional Study (Preprint). Journal of Medical Internet Research 2023 View
  12. Durieux B, Davis J, Moons P, Van Bulck L. How to get the most out of ChatGPT? Tips and tricks on prompting. European Journal of Cardiovascular Nursing 2024 View
  13. Wang L, Chen X, Deng X, Wen H, You M, Liu W, Li Q, Li J. Prompt engineering in consistency and reliability with the evidence-based guideline for LLMs. npj Digital Medicine 2024;7(1) View
  14. Huber S, Kiili K, Nebel S, Ryan R, Sailer M, Ninaus M. Leveraging the Potential of Large Language Models in Education Through Playful and Game-Based Learning. Educational Psychology Review 2024;36(1) View
  15. Liu S, McCoy A, Wright A, Nelson S, Huang S, Ahmad H, Carro S, Franklin J, Brogan J, Wright A. Why do users override alerts? Utilizing large language model to summarize comments and optimize clinical decision support. Journal of the American Medical Informatics Association 2024 View
  16. Ghanem Y, Rouhi A, Al-Houssan A, Saleh Z, Moccia M, Joshi H, Dumon K, Hong Y, Spitz F, Joshi A, Kwiatt M. Dr. Google to Dr. ChatGPT: assessing the content and quality of artificial intelligence-generated medical information on appendicitis. Surgical Endoscopy 2024 View
  17. Chiu T, Ahmad Z, Ismailov M, Sanusi I. What are artificial intelligence literacy and competency? A comprehensive framework to support them. Computers and Education Open 2024;6:100171 View
  18. Kaba E, Solak M, Çeliker F. The Role of Prompt Engineering in Radiology Applications of Generative AI. Academic Radiology 2024 View
  19. Sarangi P, Mondal H. Response Generated by Large Language Models Depends on the Structure of the Prompt. Indian Journal of Radiology and Imaging 2024 View
  20. Chen J, Granet D. Prompt Engineering: Helping ChatGPT Respond Better to Patients and Parents. Journal of Pediatric Ophthalmology & Strabismus 2024;61(2):148 View
  21. Sewunetie W, Kovács L. Exploring Sentence Parsing: OpenAI API-Based and Hybrid Parser-Based Approaches. IEEE Access 2024;12:38801 View
  22. Kaba E, Vogl T. RE: Accuracy of Large Language Models in Answering ESUR Guidelines on Contrast Media-Related Questions. Academic Radiology 2024 View
  23. Caglayan A, Slusarczyk W, Rabbani R, Ghose A, Papadopoulos V, Boussios S. Large Language Models in Oncology: Revolution or Cause for Concern?. Current Oncology 2024;31(4):1817 View
  24. Huang Y, Wu R, He J, Xiang Y. Evaluating ChatGPT-4.0’s data analytic proficiency in epidemiological studies: A comparative analysis with SAS, SPSS, and R. Journal of Global Health 2024;14 View
  25. Cheng J. Applications of Large Language Models in Pathology. Bioengineering 2024;11(4):342 View
  26. Lin K, Chen T, Lin M, Chen Y, Chen T. Integration and Assessment of ChatGPT in Medical Case Reporting: A Multifaceted Approach. European Journal of Investigation in Health, Psychology and Education 2024;14(4):888 View
  27. Artsi Y, Sorin V, Konen E, Glicksberg B, Nadkarni G, Klang E. Large language models for generating medical examinations: systematic review. BMC Medical Education 2024;24(1) View

Books/Policy Documents

  1. Hu Y, Kurylo A. The Role of Generative AI in the Communication Classroom. View