AI/ML-enabled medical device firms paid $39.7 million for radiology devices from 2017–2023, raising transparency concerns.
Key Details
- 1AI/ML-enabled medical device developers paid $39.7M for radiology devices over seven years.
- 2Total industry payments to healthcare entities reached $179M in the same period; only cardiovascular devices saw more ($59.4M).
- 3Researchers identified 846 FDA-listed AI/ML-enabled medical devices, but only 79 (9.3%) disclosed payment data.
- 4Annual payments rose from $17.3M in 2017 to $24.6M in 2023, with general payments doubling from $6.6M to $13.3M.
- 5The number of physician and hospital payment recipients more than doubled, but most manufacturers reported no payments.
- 6Study suggests underreporting may occur due to differing device clearance, reimbursement, and classification pathways.
Why It Matters
Financial incentives from AI device manufacturers may influence adoption and promotion decisions in radiology, underlining the importance of transparency. Calls for modernized disclosure requirements could affect radiology-AI industry practices and regulatory oversight.

Source
AuntMinnie
Related News

•AuntMinnie
Experts Call for Stricter FDA Standards in Radiology AI Validation
Dana-Farber experts recommend actionable steps to enhance the rigor and transparency of FDA validation standards for radiology AI software.

•AuntMinnie
Head-to-Head Study Evaluates AI Accuracy in Fracture Detection on X-Ray
A prospective study compared three commercial AI tools for fracture detection on x-ray, showing moderate-to-high accuracy for simple cases but weaker performance in complex scenarios.

•AuntMinnie
AI Boosts Agreement in CAD-RADS Classification on Cardiac CT
Deep learning AI improves interreader agreement in CAD-RADS assessments on coronary CT angiography.