Knowledge, Attitude, And Practice of Artificial Intelligence Among Undergraduate Medical Students: A Cross-Sectional Study

Background: Artificial Intelligence (AI) is revolutionizing the medical field, with applications in medical imaging, patient management, and predictive analytics. With the increasing presence of AI in medicine, medical students need to be imparted with knowledge, a good attitude, and proper practices in order to incorporate AI into clinical decision-making. Objectives: The purpose of this study is to assess the knowledge, attitude, and practice (KAP) of undergraduate medical students towards AI, determining gaps and areas of improvement in medical education. Methods: A cross-sectional study was carried out among 250 undergraduate medical students. A structured questionnaire with 21 items (7 each for knowledge, attitude, and practice) was administered, with responses noted on a five-point Likert scale. Descriptive statistics were used to analyze the data. Results: A good 65% of the participants had excellent familiarity with AI, particularly in medicine imaging and diagnostics. Just 40% understood AI usage in drug discovery and genomics, though. A 72% majority was certain that AI would enhance healthcare and that 68% wanted training in AI. Still, a 55% majority was anxious that AI would decrease clinical thinking. In terms of practice, only 35% had previously used AI-based tools for medical learning, and 48% were unsure how to apply AI in clinical settings. Conclusion: While students show a positive attitude toward AI, gaps exist in knowledge and practical implementation. Integrating AI education into the medical curriculum is necessary to enhance competency. Further research should assess the long-term impact of AI exposure on medical training.