Covera Health has announced a partnership with Advanced Radiology Services (ARS), aligning the physician-owned Michigan practice with Covera's national Quality Care Program.
The partnership entails ARS joining Covera's Agency for Healthcare Research and Quality (AHRQ)-certified Patient Safety Organization and national analytics platform, benchmarking, and continuous improvement across subspecialties, the firm said. It also includes using Covera's AI infrastructure to surface "clinically meaningful findings" that can improve outcomes for patients at risk for complex or progressive diseases, such as osteoporosis and chronic obstructive pulmonary disease.
ARS serves six healthcare systems in Michigan and interprets over 2.5 million studies annually. The practice will collaborate with Covera to "enhance diagnostic performance measurement, develop radiology quality metrics that matter, and apply artificial intelligence to better identify high-risk patients who could benefit from early intervention and improved follow-up care," Covera noted.
The initiative is led by ARS President Ryan Duhn, MD, and Executive Vice President Andy Moriarity, MD.















![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&fit=crop&h=112&q=70&w=112)



