
A new study finds fewer than 30% of FDA-cleared AI medical devices reported key safety or adverse event data before approval.
Key Details
- 1Study reviewed FDA data for AI/ML devices cleared between 1995 and July 2023.
- 2Out of 691 devices analyzed, 531 were radiology-specific.
- 3Fewer than 30% of devices shared safety or adverse event information prior to clearance.
- 4Authors call for more stringent testing and clearer regulatory standards.
- 5Lack of predefined efficacy and risk standards highlighted as a critical issue.
Why It Matters
Radiology relies heavily on AI devices, making their safety and efficacy crucial to patient care. The study urges tighter oversight and transparency, which could directly impact how radiologists incorporate AI into practice.

Source
Health Imaging
Related News

•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.

•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.

•AuntMinnie
AI Algorithm Streamlines and Standardizes Shoulder Ultrasound Acquisition
A multitask AI system demonstrated high accuracy in standardizing and guiding shoulder musculoskeletal ultrasound imaging.