TY  - JOUR
AU  - Alkhaaldi, Saif M I
AU  - Kassab, Carl H
AU  - Dimassi, Zakia
AU  - Oyoun Alsoud, Leen
AU  - Al Fahim, Maha
AU  - Al Hageh, Cynthia
AU  - Ibrahim, Halah
PY  - 2023
DA  - 2023/12/22
TI  - Medical Student Experiences and Perceptions of ChatGPT and Artificial Intelligence: Cross-Sectional Study
JO  - JMIR Med Educ
SP  - e51302
VL  - 9
KW  - medical education
KW  - ChatGPT
KW  - artificial intelligence
KW  - large language models
KW  - LLMs
KW  - AI
KW  - medical student
KW  - medical students
KW  - cross-sectional study
KW  - training
KW  - technology
KW  - medicine
KW  - health care professionals
KW  - risk
KW  - education
AB  - Background: Artificial intelligence (AI) has the potential to revolutionize the way medicine is learned, taught, and practiced, and medical education must prepare learners for these inevitable changes. Academic medicine has, however, been slow to embrace recent AI advances. Since its launch in November 2022, ChatGPT has emerged as a fast and user-friendly large language model that can assist health care professionals, medical educators, students, trainees, and patients. While many studies focus on the technology’s capabilities, potential, and risks, there is a gap in studying the perspective of end users. Objective: The aim of this study was to gauge the experiences and perspectives of graduating medical students on ChatGPT and AI in their training and future careers. Methods: A cross-sectional web-based survey of recently graduated medical students was conducted in an international academic medical center between May 5, 2023, and June 13, 2023. Descriptive statistics were used to tabulate variable frequencies. Results: Of 325 applicants to the residency programs, 265 completed the survey (an 81.5% response rate). The vast majority of respondents denied using ChatGPT in medical school, with 20.4% (n=54) using it to help complete written assessments and only 9.4% using the technology in their clinical work (n=25). More students planned to use it during residency, primarily for exploring new medical topics and research (n=168, 63.4%) and exam preparation (n=151, 57%). Male students were significantly more likely to believe that AI will improve diagnostic accuracy (n=47, 51.7% vs n=69, 39.7%; P=.001), reduce medical error (n=53, 58.2% vs n=71, 40.8%; P=.002), and improve patient care (n=60, 65.9% vs n=95, 54.6%; P=.007). Previous experience with AI was significantly associated with positive AI perception in terms of improving patient care, decreasing medical errors and misdiagnoses, and increasing the accuracy of diagnoses (P=.001, P<.001, P=.008, respectively). Conclusions: The surveyed medical students had minimal formal and informal experience with AI tools and limited perceptions of the potential uses of AI in health care but had overall positive views of ChatGPT and AI and were optimistic about the future of AI in medical education and health care. Structured curricula and formal policies and guidelines are needed to adequately prepare medical learners for the forthcoming integration of AI in medicine. 
SN  - 2369-3762
UR  - https://mededu.jmir.org/2023/1/e51302
UR  - https://doi.org/10.2196/51302
UR  - http://www.ncbi.nlm.nih.gov/pubmed/38133911
DO  - 10.2196/51302
ID  - info:doi/10.2196/51302
ER  -