A cross-sectional study on attitude and understanding of artificial intelligence and its use in medical education among medical students in a tertiary care teaching hospital
Year: 2025
Type: article
Study design: Observational Study
Abstract: Background: Artificial intelligence (AI) has the potential to revolutionize medical education by enhancing diagnostic accuracy, improving decision-making and streamlining healthcare delivery. Aims and objectives of the study were to assess the attitude towards the use of AI in medical education and to evaluate the level of understanding of AI concepts among medical students along with identification of factors influencing their attitudes and understanding of AI. Methods: A cross-sectional study was undertaken at a tertiary care teaching hospital after taking institutional ethics committee (IEC) approval. A total of 250 medical students from various academic years were included in the study. A self-made structured questionnaire was administered to collect data on student’s demographic characteristics, attitudes towards AI, understanding of AI concepts and their readiness to integrate AI into their future practice. Data were later analyzed using appropriate statistical tests. Results: Majority of students were aware of AI. Most students acknowledged AI’s potential to enhance medical learning, particularly in diagnostics (76%) and nearly half (45%) of students expressed concerns about AI replacing human judgment in clinical decision-making. Moreover, the study found a significant gap in formal education on AI with majority of students stating that AI was not adequately addressed in their curriculum. Conclusions: While medical students recognize the transformative potential of AI in healthcare, there is a clear need for enhanced AI education within medical curricula. So, this study highlights the importance of integrating AI-related content into medical education to prepare students for the evolving landscape of healthcare.
Authors: Asra Kichloo, Shabnam Choudhary
Institutions: Government Medical College, Government Medical College
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4411128141