
US healthcare executives call for a single federal AI policy framework to streamline adoption and overcome regulatory obstacles, citing specific imaging AI use cases.
Key Details
- 1Healthcare Leadership Council surveyed 27 member organizations, spanning providers, insurers, pharma, and tech.
- 2Executives warn that varying state-level rules hinder AI progress and patient care improvement.
- 3Cited barriers: inconsistent regulations, data access challenges, capability and trust gaps.
- 4Recommendations include centralized federal legislation, standardizing data and interoperability, and workforce AI upskilling.
- 5Report highlights radiology as a key AI use case, stressing the need for diverse and representative training data.
- 6Executive order from the White House has sought to address state regulatory fragmentation.
Why It Matters

Source
Radiology Business
Related News

Russia Launches Nationwide MosMed.AI Platform for Radiology AI Standardization
Russia has launched the MosMed.AI platform to standardize and expand the use of healthcare AI, with a focus on radiology.

Stanford AI Lab and Rad Partners Form Alliance to Monitor Imaging AI
Stanford Radiology's AI Lab and Rad Partners announce a partnership to develop and share best practices for assessing and monitoring AI in medical imaging.

AI Automates CPT Coding for Interventional Radiology Procedures
Large language models like XLNet show promise in automating CPT code assignment for interventional radiology procedures.