Upskilling or deskilling? Measurable role of an AI-supported training for radiology residents: a lesson from the pandemic.

ABSTRACT:

Objectives

This article aims to evaluate the use and effects of an artificial intelligence system supporting a critical diagnostic task during radiology resident training, addressing a research gap in this field.

Materials and methods

We involved eight residents evaluating 150 CXRs in three scenarios: no AI, on-demand AI, and integrated-AI. The considered task was the assessment of a multi-regional severity score of lung compromise in patients affected by COVID-19. The chosen artificial intelligence tool, fully integrated in the RIS/PACS, demonstrated superior performance in scoring compared to the average radiologist. Using quantitative metrics and questionnaires, we measured the 'upskilling' effects of using AI support and residents' resilience to 'deskilling,' i.e., their

SUBMITTER: Savardi M 

PROVIDER: S-EPMC11780016 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature