Perception of Medical Students and Faculty Regarding the Use of Artificial Intelligence (AI) in Medical Education: A Cross-Sectional Study

Abstract

Introduction Artificial intelligence (AI) is revolutionizing healthcare, offering opportunities to improve diagnosis, clinical care, and medical education. Despite its growing importance, familiarity with AI in medical education remains limited, necessitating a deeper understanding of perceptions among medical students and faculty. The aim of the study is to explore the perceptions of medical students and faculty regarding the use of AI in medical education and its implications for curriculum improvement. Materials and methods A cross-sectional study was conducted over six months (January-June 2024) at Sheikh Bhikhari Medical College, Hazaribagh, India. An online questionnaire was distributed to 299 participants, including 242 (80.93%) students, 20 (6.68%) residents, and 37 (12.04%) faculty members, using convenience sampling. Data was analyzed using IBM SPSS Statistics for Windows, Version 26 (Released 2019; IBM Corp., Armonk, NY, USA). Results The results revealed that 260 (86.95%) understood AI concepts, but only 36 (12.04%) were very familiar with its application in education. Additionally, 260 (87%) supported AI integration into medical curricula, and 273 (91.3%) believed it could improve educational efficiency. However, 179 (59.9%) had no prior experience with AI tools. Participants highlighted AI's potential in diagnostics (154, or 51.5%), clinical reasoning (51, or 17.1%), radiology (50, or 16.7%), pathology (31, or 10.4%), and 265 (88.62%) expressed a desire for structured AI training. Discussion While enthusiasm for AI integration is evident, gaps in exposure and structured education persist. Similar findings in global studies underline the urgent need for standardized curricula and faculty training. Conclusion This study highlights the importance of incorporating AI in medical education to prepare healthcare professionals for future challenges. Addressing gaps in knowledge and providing practical exposure are crucial for leveraging AI's full potential in medicine. Further multi-center studies are recommended to validate these findings.

Ähnliche Arbeiten