August 31, 2022Open Access

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

Key Points

Key points are not available for this paper at this time.

Abstract

These findings suggest that AI-aided interpretation was associated with improved reader performance and efficiency for identifying major thoracic findings on a chest radiograph.

Bookmark

View Full Paper

Cite This Study

Ahn et al. (Wed,) studied this question.

synapsesocial.com/papers/6987c7cab653197e93c17809 https://doi.org/https://doi.org/10.1001/jamanetworkopen.2022.29289

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

1Development and validation of a deep learning algorithm detecting 10 common abnormalities on chest radiographs2020 · 99 citations
2Reader Variability in Identifying Pulmonary Nodules on Chest Radiographs From the National Lung Screening Trial2012 · 26 citations
3ACR Appropriateness Criteria® Routine Chest Radiography2016 · 45 citations
4Intraobserver and interobserver agreement of the interpretation of pediatric chest radiographs2010 · 99 citations
5Deep Residual Learning for Image Recognition2016 · 221,744 citations

Bookmark

View Full Paper