Integrating Artificial Intelligence into Radiology: A Meta-Analysis of Educational Interventions and Technological Trends
Presentation Type
Poster
Student
No
Track
Health Care Application
Abstract
Radiology, a vital field in medical diagnostics, is transforming with the increasing integration of Artificial Intelligence (AI) into clinical workflows and transforming the roles and responsibilities of radiologists. These professionals, known for their prestige, autonomy, and socially respected positions, face significant transitions as AI becomes an integral part of their work. Effective educational interventions are essential to support this shift and ensure a smooth integration of AI technologies into radiologists' roles.
This PRISMA-based meta-analysis synthesizes findings from systematic literature reviews (SLRs) to explore the types of AI technologies used in radiology and the educational strategies implemented to facilitate their adoption. Covering academic publications from January 2019 to December 2024, the study categorizes radiologists’ roles, the AI technologies employed, and the educational support provided.
The analysis underscores the evolving applications of AI in radiology and highlights the critical role of targeted education in bridging the gap between technology and practice. This research offers valuable insights for practitioners and Information Systems (IS) researchers by identifying trends and gaps in the literature. It concludes with recommendations for tailoring educational interventions to address the unique demands of radiologists' professional roles and enhance the integration of AI into their workflows.
Start Date
2-7-2025 1:00 PM
End Date
2-7-2025 2:30 PM
Integrating Artificial Intelligence into Radiology: A Meta-Analysis of Educational Interventions and Technological Trends
Volstorff A
Radiology, a vital field in medical diagnostics, is transforming with the increasing integration of Artificial Intelligence (AI) into clinical workflows and transforming the roles and responsibilities of radiologists. These professionals, known for their prestige, autonomy, and socially respected positions, face significant transitions as AI becomes an integral part of their work. Effective educational interventions are essential to support this shift and ensure a smooth integration of AI technologies into radiologists' roles.
This PRISMA-based meta-analysis synthesizes findings from systematic literature reviews (SLRs) to explore the types of AI technologies used in radiology and the educational strategies implemented to facilitate their adoption. Covering academic publications from January 2019 to December 2024, the study categorizes radiologists’ roles, the AI technologies employed, and the educational support provided.
The analysis underscores the evolving applications of AI in radiology and highlights the critical role of targeted education in bridging the gap between technology and practice. This research offers valuable insights for practitioners and Information Systems (IS) researchers by identifying trends and gaps in the literature. It concludes with recommendations for tailoring educational interventions to address the unique demands of radiologists' professional roles and enhance the integration of AI into their workflows.