The RSNA has launched the Screening Mammography Breast Cancer Detection Artificial Intelligence (AI) Challenge, the latest in a series of research competitions the association first initiated in 2015.
The competitors will be evaluated on their ability to develop AI software to aid in finding breast cancer on screening mammography images from a dataset contributed by mammography screening programs in Australia and the U.S.
The accuracy of machine-learning models developed by the contestants will be evaluated against this ground truth dataset, which includes detailed labels, with radiologists' evaluations, and follow-up pathology results for suspected malignancies.
The dataset will remain available for use in further research at the conclusion of the challenge, scheduled to end March 31, 2023.
This challenge is part of a broader research project that will examine how models generated in the competition perform against previously unseen data and compare their performance to that of expert human observers. These questions are critical in determining how AI tools will perform in clinical settings, notes the RSNA.
![A normal mammogram confirmed by three-year radiologic follow-up illustrates reader-marked regions of interest (ROIs) during (A) unaided (round 1) and (B) artificial intelligence (AI)–assisted (round 2) reading. Each colored dot represents an ROI for recall by a human reader. Readers could mark more than one ROI per case, represented by multiple dots of the same color. During AI-assisted reading, the AI system displayed three visible prompts: two with suspicion of malignancy scores of 35% (left mediolateral oblique [L MLO] and craniocaudal [L CC]) and one with a suspicion of malignancy score of 10% (right craniocaudal [R CC]), shown as polygonal overlays. Without AI, six of 10 readers (60%) marked a false-positive ROI. With AI assistance, this fell to two of 10 (20%). R MLO = right mediolateral oblique.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/07/2026-07-14-radiology-mammogram-ai-auto-bias.H0bYO8QlWs.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
