A Survey-Based Cross-Sectional Study of Undergraduate Medical Students' Expectations for Medical Education and Attitudes Regarding Artificial Intelligence in Medicine

Abstract

Background: Medical technologies have been revolutionized by artificial intelligence (AI), which is widely recognized as a field of computer science that can solve challenging issues. Assessing medical students' acceptance and potential use of AIEd (Artificial Intelligence in Education) is essential in understanding the advantages and challenges of AI in medical education and promoting its successful integration. Understanding medical students' attitudes toward AI is also crucial in influencing their behaviour in the future. This cross-sectional study was carried out among undergraduate medical students in light of the described data in order to evaluate their knowledge, confidence, and perceived dependability of AI as well as their preferences for training related to AI. Materials and Methods: The study was conducted in a Tertiary Care Hospital at Puducherry. Convenience sampling was used to choose undergraduate medical students who met the study's qualifying requirements. A validated and pre-tested semi-structured questionnaire was used to gather data for the study. It has five sections: socio-demographic information, knowledge of artificial intelligence in medicine, attitudes toward AI in medicine, expectations for AI in medical education, and open-ended questions about opinions on AI in medical education. The data collected were entered in Microsoft Excel 2019 and the results were analyzed using SPSS software version 23.0 Results: The study found that most undergraduate medical students have neutral to generally positive opinions regarding AI and acknowledge its potential for help in diagnosis and therapy. The perceptions of the majority of participants may have been influenced by their lack of prior exposure to AI-related courses or real-world applications. Conclusion: In order to prepare aspiring doctors for the quickly changing technological landscape in healthcare, the results highlight the significance of including organized AI education in the medical curriculum.

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