Improving Breast Cancer Detection Accuracy of Mammography with the Concurrent Use of an Artificial Intelligence Tool.

ABSTRACT:

Purpose

To evaluate the benefits of an artificial intelligence (AI)-based tool for two-dimensional mammography in the breast cancer detection process.

Materials and methods

In this multireader, multicase retrospective study, 14 radiologists assessed a dataset of 240 digital mammography images, acquired between 2013 and 2016, using a counterbalance design in which half of the dataset was read without AI and the other half with the help of AI during a first session and vice versa during a second session, which was separated from the first by a washout period. Area under the receiver operating characteristic curve (AUC), sensitivity, specificity, and reading time were assessed as endpoints.

Results

The average AUC across readers was 0.769 (95% CI: 0.724, 0.814) without A

SUBMITTER: Pacile S 

PROVIDER: S-EPMC8082372 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature