Pathways to breast cancer screening artificial intelligence algorithm validation
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Updated: Jan 19, 2026

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
Published on: July 11, 2025
Christoph I Lee1, Nehmat Houssami2, Joann G Elmore3
1Department of Radiology, University of Washington School of Medicine, Department of Health Services, University of Washington School of Public Health, Hutchinson Institute for Cancer Outcomes Research, Seattle, WA, USA.
Abstract:
As more artificial intelligence (AI)-enhanced mammography screening tools enter the clinical market, greater focus will be placed on external validation in diverse patient populations. In this viewpoint, we outline lessons learned from prior efforts in this field, the need to validate algorithms on newer screening technologies and diverse patient populations, and conclude by discussing the need for a framework for continuous monitoring and recalibration of these AI tools. Sufficient validation and continuous monitoring of emerging AI tools for breast cancer screening will require greater stakeholder engagement and the creation of shared policies and guidelines.

