Health AI Central
Share:
Peer-Reviewed Publication
J Breast Imaging2025;7(1):45-53.January 25, 2025Journal Article

Potential Impact of an Artificial Intelligence-based Mammography Triage Algorithm on Performance and Workload in a Population-based Screening Sample.

Alyssa T Watanabe1,2, Hoanh Vu2, Chi Y Chim2, Andrew W Litt3, Tara Retson4, Ray C Mayo5
1Department of Radiology, Keck School of Medicine, University of Southern California (USC), Los Angeles, CA, USA.
2CureMetrix Incorporated, San Diego, CA, USA.
3Cornice Health Ventures, LLC, Miami Beach FL, USA.
4Department of Radiology, University of California San Diego (UCSD), La Jolla, CA, USA.
5Department of Breast Imaging, University of Texas MD Anderson Cancer Center, Houston, TX, USA.
PubMed DOI

Abstract

OBJECTIVE: To evaluate potential screening mammography performance and workload impact using a commercial artificial intelligence (AI)-based triage device in a population-based screening sample. METHODS: In this retrospective study, a sample of 2129 women who underwent screening mammograms were evaluated. The performance of a commercial AI-based triage device was compared with radiologists' repor…

Create a free account to keep reading

Free members get 10 full research views every month across publications, clinical trials, FDA clearances, adverse events, and NIH grants. No credit card required.

Create Free AccountSign In

Want unlimited research access? See Pro plans

Data Accuracy Notice: Research intelligence on Health AI Central is aggregated from public sources (PubMed, ClinicalTrials.gov, FDA, NIH, CMS, and others) and refreshed nightly. Classifications and derived metrics are produced by automated methods described in our Methodology. We recommend verifying critical data points against the primary sources before making decisions.