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
Deep Learning Improves Dual-Energy CT Venography for Liver Transplants
Deep-learning image reconstruction significantly enhances image quality in dual-energy CT portal venography, aiding liver transplant planning.

•AuntMinnie
AI Enhancement Dramatically Improves Quality of Suboptimal Chest CTs
AI-powered image enhancement significantly boosts the diagnostic quality of suboptimal chest CT and CTPA studies.

•AuntMinnie
AI Enables Safe 75% Gadolinium Reduction in Breast MRI Without Losing Sensitivity
AI-enhanced breast MRI with a 75% reduced gadolinium dose maintained diagnostic sensitivity comparable to full-dose protocols.