RSNA Ventures Launches, Partners with Rad AI to Integrate Generative AI in Radiology Workflow

The Radiological Society of North America (RSNA) has made a significant move in the field of radiology by launching RSNA Ventures, a new subsidiary aimed at accelerating innovation in medical imaging. In a strategic partnership, RSNA Ventures has joined forces with Rad AI, a leader in generative AI solutions for radiology, to integrate RSNA's extensive peer-reviewed knowledge directly into radiologists' workflows.

RSNA Ventures: A Launchpad for Radiology Innovation

RSNA Ventures, unveiled last week, is designed to be a catalyst for new ideas that will drive meaningful impact in radiology and imaging. Dr. Adam Flanders, who serves on the RSNA board of directors as the liaison for information technology, explained that the venture arm's mission is to enhance the practice of radiology, improve patient care, and advance the field of medical imaging.

The launch of RSNA Ventures comes at a critical time for the radiology field, which is facing increasing challenges. A widening gap between rising demand and limited workforce capacity has led to shortages in diagnostic radiology. Radiologists are grappling with growing case volumes and complexity, compounded by workforce shortages.

Rad AI Partnership: Bringing AI-Powered Solutions to Radiologists

The partnership between RSNA Ventures and Rad AI marks a significant step towards addressing these challenges. Rad AI, founded in 2018 by Dr. Jeff Chang, one of the youngest U.S. radiologists in history, has developed generative AI tools specifically for radiology to streamline workflows and reduce burnout.

Key features of the partnership include:

• Integration of RSNA's peer-reviewed content, spanning 100 years, into Rad AI's existing solutions used across U.S. radiology practices and health systems.
• Automatic generation of report impressions from dictated findings using Rad AI's Impressions tool.
• Advanced machine learning algorithms and generative AI to create accurate reports quickly through Rad AI's Reporting solution.
• Closing the loop on follow-up recommendations for significant incidental findings using Rad AI's Continuity feature.

The collaboration aims to provide radiologists with immediate access to trusted, peer-reviewed, relevant information at the point of interpretation. This integration is expected to help manage growing workloads while maintaining high standards of care.

Impact and Future Outlook

Rad AI's solutions have shown promising results, with claims of saving radiologists more than 60 minutes per shift and reducing dictation time by nearly half. The company reports that 84% of radiologists using its products cite reduced burnout and have dictated up to 35% fewer words.

The partnership's first milestone will be a product demonstration at the RSNA 2025 annual meeting in Chicago in late November. As the radiology field continues to evolve, collaborations like this between practitioners and technology providers are expected to play a crucial role in shaping the future of medical imaging and patient care.