
A new study finds that under 30% of radiology-focused AI/ML devices authorized by the FDA had clinical testing prior to authorization.
Key Details
- 1FDA has cleared over 1,000 AI/ML devices, most for radiology.
- 2Research published in JAMA Network Open reviewed almost 1,000 algorithms approved from 1995 to June 2024.
- 3Of 723 radiology devices, fewer than 30% underwent any form of clinical testing.
- 4Very few devices were subject to prospective trials before clearance.
- 5Authors highlight a lack of standards for safety and efficacy in FDA authorization of AI/ML devices.
Why It Matters
The rapid proliferation of AI/ML devices in radiology without adequate clinical validation raises concerns about patient safety and efficacy. The findings emphasize an urgent need for more rigorous regulatory oversight and defined testing standards for imaging AI tools.

Source
Radiology Business
Related News

•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
UCLA Review Evaluates Breast AI for Early Cancer Detection
A UCLA-led review analyzes current evidence for AI tools in screening mammography, focusing on their capability to detect interval cancers.

•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.