Health AI Central
Share:
Peer-Reviewed Publication
BJR Artif Intell2025;2(1):ubaf004.January 1, 2025Journal Article

Artificial intelligence and consistency in patient care: a large-scale longitudinal study of mammographic density assessment.

Susan O Holley1, Daniel Cardoza2, Thomas P Matthews2, Elisha E Tibatemwa3, Rodrigo Morales Hoil2, Adetunji T Toriola4,5, Aimilia Gastounioti3,5
1Onsite Women's Health, Nashville, TN 37203, United States.
2Whiterabbit.ai, Redwood City, CA 94065, United States.
3Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63110, United States.
4Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, MO 63110, United States.
5Siteman Cancer Center, Barnes-Jewish Hospital, Washington University School of Medicine, St. Louis, MO 63110, United States.
PubMed PMC DOI PDF

Abstract

OBJECTIVES: To assess whether use of an artificial intelligence (AI) model for mammography could result in more longitudinally consistent breast density assessments compared with interpreting radiologists. METHODS: The AI model was evaluated retrospectively on a large mammography dataset including 50 sites across the United States from an outpatient radiology practice. Examinations were acquired…

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.