Viz.ai is collaborating with the National Rural Health Association (NRHA) to help rural hospital leaders understand and implement AI tools for disease detection and care coordination.
As part of the collaboration, Viz.ai and the NRHA will provide educational webinars, real-world case studies, and programming at the NRHA's national conference in May. Viz.ai's platform analyzes medical images and clinical data to identify conditions including stroke, pulmonary embolism, and aortic disease, automatically alerting clinicians and connecting local teams with specialists.
Viz.ai said the collaboration is intended to address a gap in rural AI adoption, citing research showing rural hospitals are 25% less likely to adopt new technologies such as AI than urban organizations due to funding and access constraints. The platform is currently used in 2,000 hospitals across the U.S., according to the company.
![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)
