Knowledge, fear and application of artificial intelligence in healthcare and learning, analysis of undergraduate medical students' perspective

Abstract

Background: Artificial Intelligence (AI) is increasingly integrated into healthcare and medical education. Understanding how future healthcare professionals perceive this transformation is crucial for shaping curricula and policy. Methods: A multicentric, cross-sectional analytical study was conducted using a structured, anonymous online questionnaire. The survey comprised 15 multiple-choice questions across three domains: AI knowledge, concerns about its adoption, and expectations of its role in clinical practice and education. A total of 403 MBBS students participated. Descriptive and inferential statistics were used to analyse the data. Results: Most students (75.7%) recognized AI's potential in predicting patient outcomes, and 76.7% believed AI could support but not replace clinical judgment. Ethical and privacy issues (54.3%) were the most cited integration barriers. While 63.3% viewed AI-driven decision support systems positively, 61.8% feared AI might replace doctors—especially due to reduced human interaction (40.9%). Limited practical exposure was evident; 44.4% had never used AI tools, though 86.4% expressed interest in learning more. A majority (67.2%) prioritized human intuition over data-driven decision-making. Conclusions: MBBS students show positive attitudes and curiosity toward AI but have limited practical exposure and formal training. The findings highlight the urgent need to integrate AI education into medical curricula to prepare students for its ethical and clinical implications.

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