Medical Students' Perceptions of Artificial Intelligence Use in Medical Practice: A Systematic Review

Artificial intelligence (AI) is rapidly transforming the medical field, including diagnostics, workflow, and treatment. Despite its possible benefits, medical students hold varied perceptions regarding AI's role in clinical practice, raising concerns about its integration into medical education.

This study aims to evaluate medical students' perspectives on AI in medicine, focusing on its impact on medical education, specialty selection, and job security.

A systematic review was conducted using four electronic databases-PubMed, CINAHL, ERIC, and Scopus-resulting in 3,693 articles. After removing duplicates and applying inclusion criteria, 11 articles were selected for analysis. Studies were assessed based on their results, evidence quality, and discussion of ethical considerations using a 6-point scoring system. Data extraction focused on AI-related perceptions, specialty choices, and suggestions for improving curriculum.

This review shows mixed perceptions among medical students. While many expressed concerns about job security and AI's role in replacing physician tasks, especially in the field of radiology, others highlighted more optimistic opinions such as AI's ability to enhance diagnostic accuracy, streamline workflows, and reduce burnout. Students emphasized the need for structured AI education, as well as major ethical concerns, such as bias in AI algorithms, and the need for clear accountability frameworks.

AI in medicine appears to encourage both optimism and apprehension among medical students. While students realize its potential, the issue of job displacement and insufficient education on AI in the field persist. Incorporating AI-focused curricula in medical schools could address this, allowing future physicians to work alongside AI systems effectively.