人工智能对加拿大医学生和住院医师放射科专业偏好的影响

RATIONALE AND OBJECTIVES: Artificial intelligence (AI) is playing an increasingly significant role in radiology While prior studies examined medical student perceptions of AI, they predate recent advances and don't capture resident perspectives. This study reassesses how AI exposure and savviness influences radiology specialty preferences among Canadian medical students and radiology residents.

MATERIALS AND METHODS: An anonymous national survey was distributed which evaluated AI exposure, understanding, and its impact on radiology interest. Respondents were stratified by interest in radiology, AI exposure, and AI-savviness, defined by correct responses to knowledge-based questions. Statistical analysis was done using logistic regression models.

RESULTS: 401 complete responses were collected. AI had minimal to moderate influence on most students' specialty preferences, though 32.9% reported discouragement from radiology due to AI. AI-savvy students were more likely to view AI as a tool that enhances radiology and were more likely to choose it as a specialty choice. However, they were also more likely to express hesitation about pursuing radiology despite their interest preferences. Participants' views on AI's role in didactic teaching, clerkship education, residency education, and research did not predict interest in radiology or AI-savviness, but participants who thought AI could play a beneficial role in didactic teaching or residency education were more likely to be previously exposed to AI.

CONCLUSION: While AI-savvy students recognize the value of AI in radiology, they are also more aware of its potential to disrupt the profession. These findings highlight the need for thoughtful AI education and clear communication to support career decision-making in an evolving field.