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Radiology, a critical field in medical diagnostics, is undergoing a profound transformation as Artificial Intelligence (AI) is integrated into radiologists' workflows. This shift is redefining the roles and responsibilities of radiologists, professionals traditionally recognized for their expertise, autonomy, and societal prestige. As AI becomes increasingly embedded in radiological practice, effective educational interventions are essential to facilitate a seamless transition and optimize technology adoption. This study employs a PRISMA-based systematic literature review (SLRs), to examine AI applications in radiology and the educational strategies designed to support their implementation. Analyzing academic publications from January 2019 to December 2024, it categorizes AI technologies, theories, evolving radiologist roles and the instructional approaches used to enhance AI proficiency. The findings highlight the expanding role of AI in radiology and underscore the necessity of targeted education to bridge the gap between technological advancements and clinical practice. This research provides valuable insights for practitioners and information systems (IS) researchers by identifying key trends and gaps in existing literature. It concludes with recommendations for designing educational interventions that align with radiologists' evolving professional needs, ensuring the effective integration of AI into their Workflows.

Publication Date

2-7-2025

Integrating Artificial Intelligence into Radiology: A Meta-Analysis of Educational Interventions and Technological Trends

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