GE HealthCare and Mass General Brigham in Boston have developed an AI algorithm designed to help increase the effectiveness and productivity of radiology operations.
The algorithm will be deployed in the schedule predictions dashboard of Mass General's Radiology Operations Module (ROM), a digital imaging tool that helps optimize scheduling, reduce cost, and free providers from administrative burden, GE said. The algorithm is intended to predict missed care opportunities and late arrivals. In preliminary tests, the algorithm was able to predict the missed care opportunities at rates of up to 96%, with limited false positives, the company noted.
This is the first AI application to be launched under a 10-year AI collaboration agreement between GE HealthCare and Mass General Brigham signed in 2017, GE said.
![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)
