Association of Artificial Intelligence-Aided Chest Radiograph Interpretation With Reader Performance and Efficiency.

ABSTRACT:

Importance

The efficient and accurate interpretation of radiologic images is paramount.

Objective

To evaluate whether a deep learning-based artificial intelligence (AI) engine used concurrently can improve reader performance and efficiency in interpreting chest radiograph abnormalities.

Design, setting, and participants

This multicenter cohort study was conducted from April to November 2021 and involved radiologists, including attending radiologists, thoracic radiology fellows, and residents, who independently participated in 2 observer performance test sessions. The sessions included a reading session with AI and a session without AI, in a randomized crossover manner with a 4-week washout period in between. The AI produced a heat map and the image-level probability o

SUBMITTER: Ahn JS 

PROVIDER: S-EPMC9434361 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature