E5486. Radiology in the Age of Artificial Intelligence: A Review and Meta-Analysis Covering Medical Students, Radiology Trainees, and Radiologists
Authors
Amir Hassankhani;
University of Southern California
Melika Amoukhteh;
University of Southern California
Ali Gholamrezanezhad;
University of Southern California
Objective:
The landscape of radiology is undergoing a transformative shift with the integration of artificial intelligence (AI) for automating tasks and enhancing abnormality detection. This evolution raises pertinent questions about the role of radiologists. It is imperative to gauge the perceptions of medical students, radiology trainees, and practicing radiologists, as it aids in their preparedness for AI integration within the radiology domain.
Materials and Methods:
Employing rigorous systematic review and meta-analysis protocols, A comprehensive literature search was conducted across PubMed, Scopus, and Web of Science databases through March 5, 2023. Eligible studies that reported relevant outcomes were considered, and pertinent data were extracted and subjected to analysis using STATA software version 17.0.
Results:
A comprehensive meta-analysis based on 21 studies unveiled that 22.36% of individuals were less inclined to choose radiology as a career due to concerns about AI impact. Medical students exhibited higher levels of concern (31.94%) in comparison to radiology trainees and radiologists (9.16%) (p < 0.01). Radiology trainees and radiologists showcased a greater foundational knowledge of AI (71.84% versus 35.38%). Medical students displayed higher rates of belief that AI poses a threat to the radiology job market (42.66% versus 6.25%, p < 0.02). The cumulative rate of respondents who subscribed to the belief that "AI will revolutionize radiology in the future" was 79.48%, with no significant distinctions based on participants' roles. Moreover, the pooled rate of respondents who advocated for the integration of AI in medical curricula stood at 81.75% among radiology trainees and radiologists, and 70.23% among medical students.
Conclusion:
These findings draw attention to escalating apprehensions about the ramifications of advancing AI in the realm of radiology, particularly among medical students. Furthermore, the discernible correlation between basic AI knowledge and attitudes towards AI within the radiology field underscores the need to address and enhance AI education.
