How is Rad AI Transforming Radiology Workflows?
The generative AI tools are focused to help radiologists streamline workflows like physician dictation and follow-up care management.
On June 9, 2026, Rad AI, the California-based generative AI radiology workflow company announced partnership with the Connecticut-based nonprofit health system, Yale New Haven Health System (YNHHS). The partnership is centered on the deployment of Rad AI’s reporting technology across the health system’s imaging network.
Dr. Elizabeth Bergey, radiologist and chief clinical officer at Rad AI, told MobiHealthNews that Yale is their first major academic health system partner.
"It's been a partnership where we've grown to trust each other and work with each other very closely to help develop a big part of what Rad AI provides now," Bergey said.
Co-Developing Radiology AI
According to the company, the generative AI tools are designed to help radiologists streamline workflows like physician dictation and follow-up care management. They also added that the reporting software facilitates quick report generation, by automating portions of the reporting process and reducing dictation time.
YNHHS' Dr. Melissa Davis, vice chair for imaging informatics, radiology and biomedical imaging and associate professor of radiology and biomedical imaging told MobiHealthNews that Rad AI stands out to radiologists with Omni Impressions, a tool that automatically generates AI-enabled report impressions from raw dictated findings.
Yale New Haven is deploying Rad AI technologies, including Omni Impressions, across its five hospitals and over 16 outpatient centers. To integrate Rad AI’s technology into YNHHS, both organizations will co-develop additional radiology-focused technologies that will be used and clinically tested at YNHHS.
Davis said that the health system's goal is not just to implement products but rather to co-develop new technologies with Rad AI that meet its specific needs.
“We are hiring the best scientists there are. We are known for making a personalized model for impressions, and that kind of base skill set is what we have, which is building custom models for radiology-specific tasks," Bergey said.
Key Takeaways
- Yale New Haven Health System partners with Rad AI to enhance radiology workflows with generative AI tools.
- Implement Omni Impressions to automate report generation and reduce dictation time for radiologists.
- Co-develop new radiology technologies tailored to YNHHS needs with Rad AI's expertise.
- Deploy Rad AI technologies across five hospitals and 16 outpatient centers for improved patient care.
- Strengthen collaboration between Yale and Rad AI for ongoing innovation in radiology practices.