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
AI Guidance Cuts Novice Ultrasound Exam Time by 34%
AI guidance significantly reduces exam times and enhances diagnostic quality for novice ultrasound operators performing shoulder exams.
•AuntMinnie
AI Models Reveal Racial Disparities in Breast Cancer Patterns
Machine learning models reveal significant racial disparities and key predictors in breast cancer incidence across diverse groups.
•Radiology Business
UCLA Appoints Inaugural Associate Dean for Health AI Strategy
UCLA has appointed Katherine P. Andriole as its first associate dean for Health AI Strategy and Innovation, with an initial focus on radiology.