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

Editorial (4) Theme Issue: ChatGPT and Generative Language Models in Medical Education (86) Chatbots and Conversational Agents (543) Artificial Intelligence (1421) Clinical Information and Decision Making (1434) Machine Learning (1501) Decision Support for Health Professionals (1210) Validity, Reliability, and Bias (94)

Published on in Vol 10 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/50174, first published .
ChatGPT in Medical Education: A Precursor for Automation Bias?

ChatGPT in Medical Education: A Precursor for Automation Bias?

ChatGPT in Medical Education: A Precursor for Automation Bias?

Authors of this article:

Tina Nguyen1 Author Orcid Image
Article Authors Cited by (7) Tweetations (8) Metrics

Journals

  1. Dsouza J. A Student’s Viewpoint on ChatGPT Use and Automation Bias in Medical Education. JMIR Medical Education 2024;10:e57696 View
  2. Cheng J. Applications of Large Language Models in Pathology. Bioengineering 2024;11(4):342 View
  3. Mehta S, Mehta N. Embracing the illusion of explanatory depth: A strategic framework for using iterative prompting for integrating large language models in healthcare education. Medical Teacher 2024:1 View
  4. Rojas-Carabali W, Agrawal R, Gutierrez-Sinisterra L, Baxter S, Cifuentes-González C, Wei Y, Abisheganaden J, Kannapiran P, Wong S, Lee B, de-la-Torre A, Agrawal R. Natural Language Processing in medicine and ophthalmology: A review for the 21st-century clinician. Asia-Pacific Journal of Ophthalmology 2024;13(4):100084 View
  5. Adams T, Claydon M. ChatGPT as a primary healthcare consultation training tool for combat medical technicians. BMJ Military Health 2024:e002722 View
  6. Al-Naser Y, Halka F, Ng B, Mountford D, Sharma S, Niure K, Yong-Hing C, Khosa F, Van der Pol C. Evaluating Artificial Intelligence Competency in Education: Performance of ChatGPT-4 in the American Registry of Radiologic Technologists (ARRT) Radiography Certification Exam. Academic Radiology 2024 View
  7. Liu F, Chang X, Zhu Q, Huang Y, Li Y, Wang H. Assessing clinical medicine students’ acceptance of large language model: based on technology acceptance model. BMC Medical Education 2024;24(1) View