A proposal to relax regulation of radiology artificial intelligence (AI) software that was floated in the final days of the Trump Administration has drawn the opposition of a number of radiology groups, including the American College of Radiology (ACR), the RSNA, and the Society for Imaging Informatics in Medicine (SIIM).
In a letter sent on March 5, the organizations urged officials at the U.S. Department of Health and Human Services (HHS) to reject the proposal by the immediate-past HHS secretary to permanently exempt certain medical devices -- including radiology AI software for detection, diagnosis, and triage applications -- from U.S. Food and Drug Administration (FDA) 510(k) premarket notification requirements.
They noted that the proposal was noteworthy for the lack of FDA involvement in drafting it. The groups also claimed it contradicted the agency's plans for enhancing oversight of AI/machine learning-enabled software.
ACR Board of Chancellors Chair Dr. Howard Fleishon said in a statement that although they don't anticipate that the current administration will implement the proposal, informatics experts must inform regulators of the potentially harmful risks from this idea in case the proposal resurfaces.
The full letter can be found on the ACR's website.
![A normal mammogram confirmed by three-year radiologic follow-up illustrates reader-marked regions of interest (ROIs) during (A) unaided (round 1) and (B) artificial intelligence (AI)–assisted (round 2) reading. Each colored dot represents an ROI for recall by a human reader. Readers could mark more than one ROI per case, represented by multiple dots of the same color. During AI-assisted reading, the AI system displayed three visible prompts: two with suspicion of malignancy scores of 35% (left mediolateral oblique [L MLO] and craniocaudal [L CC]) and one with a suspicion of malignancy score of 10% (right craniocaudal [R CC]), shown as polygonal overlays. Without AI, six of 10 readers (60%) marked a false-positive ROI. With AI assistance, this fell to two of 10 (20%). R MLO = right mediolateral oblique.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/07/2026-07-14-radiology-mammogram-ai-auto-bias.H0bYO8QlWs.jpg?auto=format%2Ccompress&fit=crop&h=100&q=70&w=100)
![A normal mammogram confirmed by three-year radiologic follow-up illustrates reader-marked regions of interest (ROIs) during (A) unaided (round 1) and (B) artificial intelligence (AI)–assisted (round 2) reading. Each colored dot represents an ROI for recall by a human reader. Readers could mark more than one ROI per case, represented by multiple dots of the same color. During AI-assisted reading, the AI system displayed three visible prompts: two with suspicion of malignancy scores of 35% (left mediolateral oblique [L MLO] and craniocaudal [L CC]) and one with a suspicion of malignancy score of 10% (right craniocaudal [R CC]), shown as polygonal overlays. Without AI, six of 10 readers (60%) marked a false-positive ROI. With AI assistance, this fell to two of 10 (20%). R MLO = right mediolateral oblique.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/07/2026-07-14-radiology-mammogram-ai-auto-bias.H0bYO8QlWs.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
