Artificial Intelligence in Medical Education- Perception Among Medical Students

Abstract

Abstract Background Artificial Intelligence( AI) is increasingly being integrated into various aspects of human life, including healthcare, with applications such as robotic surgery, virtual nursing assistants, and image analysis. Recognizing the transformative impact of AI in healthcare, the World Medical Association advocates for the inclusion of AI education in medical curricula to prepare healthcare professionals for this emerging field. This study aims to assess medical students' perceptions on AI in medicine, their preferences for structured AI training during medical education, and their understanding of the ethical dimensions associated with AI in healthcare. Materials & Methods A cross-sectional study was conducted among 325 medical students in Kerala, India using a pre-validated, semi-structured, self- administered questionnaire. The survey collected demographic information, assessed participants' prior knowledge of AI, and evaluated their self-perceived understanding of AI concepts. Participants' responded to twelve 5-point Likert scale questions regarding their perceptions on AI in medicine and expressed their opinions on the inclusion of certain AI topics in medical curricula. Results & Discussion Most participants (57.2%) viewed AI as an assistive technology, capable of reducing errors in medical practice. A significant percentage(54.2%) believed that AI could enhance the accuracy of medical decisions, while 48.6% acknowledged its potential to improve patient access to healthcare. Concerns were raised by 37.6% of participants' about the potential decrease in the need for physicians, leading to unemployment. Additionally, apprehensions were expressed regarding the impact of AI on the humanistic aspects of medicine, with 69.2% fearing a decline in the human touch. Participants' also recognized potential challenges to "trust"( 52.9%), and the patient- physician relationship(54.5%). Notably, over half of the participants' were uncertain about maintaining professional confidentiality(51.1%) and believed that AI might violate confidentiality( 53.5%). Only 3.7% felt competent enough to inform patients' about features and risks of AI. Participants' expressed a strong need for structured training in AI applications, especially on the topic of "reducing medical errors"( 76.9%), and "ethical issues" arising from the widespread use of AI in healthcare(79.4%). Conclusion This study underscores the demand among medical students for structured AI training within the undergraduate medical curriculum, emphasizing the importance of incorporating AI education to meet evolving healthcare needs. While there are widespread ethical concerns, the majority are convinced that AI can be used as an assistive technology in healthcare. The findings contribute essential insights for curriculum development and the definition of learning outcomes in AI education for medical students.