Impact of Using an AI-CAD Tool in Radiology Training

Abstract

The integration of Artificial Intelligence (AI) in radiology, particularly through Computer-Aided Detection (CAD) systems, promises significant advancements in diagnostic accuracy, workflow optimization, and educational outcomes. Despite the potential benefits, challenges such as professional deskilling, overreliance on AI, and regulatory issues are still feared. This study aims to evaluate the practical, educational, and personal implications of introducing a CAD AI-tool in radiology residency. Through a mixed-methods approach involving ten radiology residents, we want to assess the impact of AI on diagnostics, bias, workflow, and resident-supervisor interactions. In the study, we monitor and interview residents that are analyzing chest X-rays using the CAD system. Preliminary findings from pilot studies indicate a generally positive reception but highlight the need for improvements. This research seeks to provide insights into the responsible deployment of AI in radiology training.

Ähnliche Arbeiten