Assessment of Medical Students’ Perception and Knowledge Toward Artificial Intelligence and its Medical Applications among a Sample of New Giza University Students: A Cross-sectional Study

Background The rapid integration of Artificial Intelligence (AI) into clinical practice necessitates preparing future physicians for such interaction. This study assessed medical students’ knowledge, attitudes, and perceptions towards clinical AI and its integration into medical curricula and identified their preferred topics and modes of delivery for AI education. Methods A cross-sectional survey using a validated questionnaire was conducted with 334 undergraduate medical students at New Giza University, Egypt. Participants were questioned about their knowledge, attitudes, and perceptions (KAPs) toward AI in medicine, and their preferred AI topics and modes of education delivery. Chi-square testing analyzed associations between students’ responses and their demographics. Results Analysis of the responses revealed that 71.9% of students do not understand fundamental AI concepts, and 60.5% cannot cite recent clinical AI advancements. Furthermore, 69.1% express concern about AI’s ethical implications in medicine. Despite this, 89.8% recognize the importance of AI in the future of medicine and 91% desire further AI education. Preferred topics included when to use AI, strengths and weaknesses of AI, and ethics of AI. The preferred modes of education were short lectures, workshops, and symposia. No significant differences were found between students’ KAPs and their academic year. Conclusion A substantial gap exists in medical students’ knowledge and perception of AI in medicine; yet they strongly recognize its significance and are eager to learn about it for three hours or less per month. To address this, curricular developers should prioritize clinically oriented topics – AI’s clinical applications, ethical implications, and the strengths and limitations - delivered in concise, interactive formats. Key learning outcomes must include the ability to critically appraise AI technologies, evaluate their outputs, and recognize limitations. Medical educators should embed these topics into existing teaching without overburdening students, cultivating future physicians confident in using AI and navigating its ethical challenges.