Medical devices that harness the power of artificial intelligence or machine learning algorithms are rapidly transforming health care in the U.S., with the Food and Drug Administration already having authorized the marketing of more than 1,000 such devices and many more in the development pipeline. A new paper from a University of Illinois Urbana-Champaign expert in the ethical and legal challenges of AI and big data for health care argues that the regulatory framework for AI-based medical devices needs to be improved to ensure transparency and protect patients’ health.

The current lack of labeling standards for AI- or machine learning-based medical devices is an obstacle to transparency in that it prevents users from receiving essential information about the devices and their safe use, such as the race, ethnicity and gender breakdowns of the training data that was used, she said. One potential remedy is that the FDA can learn a valuable lesson from food nutrition labeling and apply it to the development of labeling standards for medical devices augmented by AI.

The push for increased transparency around AI-based medical devices is complicated not only by different regulatory issues surrounding AI but also by what constitutes a medical device in the eyes of the U.S. government. The FDA has the authority from Congress to regulate medical products such as drugs, biologics and medical devices, she said. With some exceptions, a product powered by AI or machine learning and intended for use in the diagnosis of disease or in the cure, mitigation, treatment or prevention of disease is classified as a medical device under the Federal Food, Drug, and Cosmetic Act. That way, the FDA can assess the safety and effectiveness of the device.

Source: https://news.illinois.edu/paper-fda-needs-to-develop-labeling-standards-for-ai-powered-medical-devices/