Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/52113, first published .
Assessing ChatGPT’s Mastery of Bloom’s Taxonomy Using Psychosomatic Medicine Exam Questions: Mixed-Methods Study

Assessing ChatGPT’s Mastery of Bloom’s Taxonomy Using Psychosomatic Medicine Exam Questions: Mixed-Methods Study

Assessing ChatGPT’s Mastery of Bloom’s Taxonomy Using Psychosomatic Medicine Exam Questions: Mixed-Methods Study

Journals

  1. Masters K, Benjamin J, Agrawal A, MacNeill H, Pillow M, Mehta N. Twelve tips on creating and using custom GPTs to enhance health professions education. Medical Teacher 2024;46(6):752 View
  2. Noda M, Ueno T, Koshu R, Takaso Y, Shimada M, Saito C, Sugimoto H, Fushiki H, Ito M, Nomura A, Yoshizaki T. Performance of GPT-4V in Answering the Japanese Otolaryngology Board Certification Examination Questions: Evaluation Study. JMIR Medical Education 2024;10:e57054 View
  3. Huang K. Evaluating GPT-4’s Cognitive Functions Through the Bloom Taxonomy: Insights and Clarifications. Journal of Medical Internet Research 2024;26:e56997 View
  4. Herrmann-Werner A, Festl-Wietek T, Holderried F, Herschbach L, Griewatz J, Masters K, Zipfel S, Mahling M. Authors’ Reply: “Evaluating GPT-4’s Cognitive Functions Through the Bloom Taxonomy: Insights and Clarifications”. Journal of Medical Internet Research 2024;26:e57778 View
  5. Bharatha A, Ojeh N, Fazle Rabbi A, Campbell M, Krishnamurthy K, Layne-Yarde R, Kumar A, Springer D, Connell K, Majumder M. Comparing the Performance of ChatGPT-4 and Medical Students on MCQs at Varied Levels of Bloom’s Taxonomy. Advances in Medical Education and Practice 2024;Volume 15:393 View
  6. Buldur M, Sezer B. Evaluating the accuracy of Chat Generative Pre-trained Transformer version 4 (ChatGPT-4) responses to United States Food and Drug Administration (FDA) frequently asked questions about dental amalgam. BMC Oral Health 2024;24(1) View
  7. Holderried F, Stegemann-Philipps C, Herrmann-Werner A, Festl-Wietek T, Holderried M, Eickhoff C, Mahling M. A Language Model–Powered Simulated Patient With Automated Feedback for History Taking: Prospective Study. JMIR Medical Education 2024;10:e59213 View
  8. Vidhani D, Mariappan M. Optimizing Human–AI Collaboration in Chemistry: A Case Study on Enhancing Generative AI Responses through Prompt Engineering. Chemistry 2024;6(4):723 View
  9. Kipp M. From GPT-3.5 to GPT-4.o: A Leap in AI’s Medical Exam Performance. Information 2024;15(9):543 View
  10. Zhang Q, Hou H, Ju Y, Yuan J, Zhang K, Wang H, Chen J. Category Mapping of Emergency Supplies Classification Standard Based on BERT-TextCNN. Systems 2024;12(9):358 View
  11. Boyer J, Boyer W. A Strategic Roadmap for Mitigating Generative Artificial Intelligence Hallucinations. Cureus Journals 2024 View
  12. Sallam M, Al-Salahat K, Eid H, Egger J, Puladi B. Human versus Artificial Intelligence: ChatGPT-4 Outperforming Bing, Bard, ChatGPT-3.5 and Humans in Clinical Chemistry Multiple-Choice Questions. Advances in Medical Education and Practice 2024;Volume 15:857 View
  13. Kolding S, Lundin R, Hansen L, Østergaard S. Use of generative artificial intelligence (AI) in psychiatry and mental health care: a systematic review. Acta Neuropsychiatrica 2024:1 View
  14. Boyer J, Boyer W. A Strategic Roadmap for Mitigating Generative Artificial Intelligence Hallucinations. Cureus Journals 2024 View
  15. Eisinger F, Holderried F, Mahling M, Stegemann–Philipps C, Herrmann–Werner A, Nazarenus E, Sonanini A, Guthoff M, Eickhoff C, Holderried M. What's Going On with Me and How Can I Better Manage My Health? The Potential of GPT-4 to Transform Discharge Letters into Patient-Centered Letters to Enhance Patient Safety: A Prospective, Exploratory Study (Preprint). Journal of Medical Internet Research 2024 View
  16. Ng O, Phua D, Chu J, Wilding L, Mogali S, Cleland J. Answering Patterns in SBA Items: Students, GPT3.5, and Gemini. Medical Science Educator 2024 View
  17. Luo Y, Miao Y, Zhao Y, Li J, Chen Y, Yue Y, Wu Y. Comparing the Accuracy of Two Generated Large Language Models in Identifying Health-Related Rumors or Misconceptions and the Applicability in Health Science Popularization: Proof-of-Concept Study. JMIR Formative Research 2024;8:e63188 View

Books/Policy Documents

  1. Pears M, Konstantinidis S. Disruptive Technologies in Education and Workforce Development. View