Less than 30% of FDA-cleared AI devices shared key safety and adverse event data before approval, raising regulatory concerns.
Key Details
- 1A new analysis reviewed FDA approval and recall databases for all AI/ML devices cleared from 1995 to July 2023.
- 2Of 691 devices analyzed, 531 targeted radiology applications.
- 3Fewer than 30% of devices provided data on safety, efficacy, or adverse events prior to approval.
- 4No predefined efficacy or safety reporting standards currently exist for AI/ML devices in the U.S., unlike with pharmaceuticals.
- 5The findings highlight a regulatory gap and call for stricter testing and dedicated approval pathways for AI/ML-based medical devices.
Why It Matters
This research underscores a major gap in regulatory standards and transparency for AI devices in radiology, potentially impacting patient safety and trust. Addressing these concerns could lead to more robust evidence and safer adoption of AI in clinical imaging practice.
Source
Radiology Business
Related News
•Radiology Business
Real-World Study: Radiology AI Best in Emergency and Inpatient Settings
A commercial AI tool for intracranial aneurysm detection outperformed in inpatient and emergency settings but yielded limited benefits for outpatients in a major health system study.
•Radiology Business
New Rubric Enhances Safety of AI-Generated Radiology Summaries
Researchers developed a five-factor rubric to assess the safety and quality of AI-generated, patient-friendly radiology report summaries.
•Radiology Business
AI Model Surpasses Radiologists in Detecting Subtle Hip Fractures
A new AI model outperformed radiologists in identifying difficult-to-detect femoral neck fractures on radiographs.