Radiology startup Rad AI announced its company launch November 25, on the heels of a $4 million seed round led by Google's artificial intelligence (AI)-focused venture fund Gradient Ventures.
Rad AI's software uses machine-learning algorithms to automatically generate "impression" sections of radiology reports that are customized to the preferred language of the radiologist.
Initial user surveys have indicated that the software can lead to significant reductions in error rates and turnaround times and also may reduce radiologist burnout, the company said. Early studies conducted at the Einstein Healthcare Network in Philadelphia and several radiology practices have shown time savings of 20% for interpreting CT scans and 15% for radiographs.
Rad AI will display its AI technology at the upcoming RSNA 2019 meeting in Chicago.
![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)
