
The Medical Imaging & Technology Alliance (MITA) recently applauded principles co-authored by the U.S. Food and Drug Administration (FDA) for best practices on medical devices that use artificial intelligence (AI) and machine learning.
The FDA, along with Health Canada and the United Kingdom's Medicines and Healthcare products Regulatory Agency, published "Good Machine Learning Practice for Medical Device Development: Guiding Principles" in an effort to promote "safe, effective, and high-quality" devices using AI.
The guidance hastens patient access to AI technologies, according to Patrick Hope, MITA executive director. He also wrote that MITA looks forward to working with the FDA on best use of these guidelines.
In its submitted comments, MITA also asked the FDA to engage industry stakeholders and work collectively on several items. These include characterizing clinical study participants, educating developers on known risks, appropriate user labeling and regulatory submission information, and making sure a device is suitable for its target patient population.













![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=112&q=70&w=112)





