Jason Test Article for image UploadOct 29, 2018FacebookLinkedInX (Twitter)Pinterest Add us as a preferred source on Google Test articleFacebookLinkedInX (Twitter)Pinterest Add us as a preferred source on Google Latest in HomeTau PET tracer flags early Alzheimer risk in healthy older adultsJuly 17, 2026Radiologists can identify three out of four AI-generated imagesJuly 17, 2026Women's Imaging MinnieCast, Episode 13: Partial breast irradiation in the spotlightJuly 17, 2026Radiology dominates thirty years of FDA AI device approvalsJuly 16, 2026Related StoriesHomeYouth movement sweeps radiology in 2018 Minnies awardsHomeYouth movement sweeps radiology in 2018 Minnies awardsHomeMeet the Minnies 2018 finalistsHomeMeet the Minnies 2018 finalists
![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)
