Food and Drug
FDA Introduces New AI Tool for Detecting Cancer
Powered by artificial intelligence, the tool is the latest example of the FDA’s innovation around AI and machine learning for health care-related applications.
Dr. Matthew Diamond, the chief medical officer for digital health at the FDA’s Center for Devices and Radiological Health, said that the system can identify laboratory-confirmed adenomas and carcinomas in more than 55 percent of patients, compared to 42 percent through a standard colonoscopy.
In an interview with GovernmentCIO Media & Research, Diamond noted that using AI has the potential to improve health care, allowing health care providers to provide better patient care.
When traditional screenings or surveillance methods are combined with AI, the next-generation technology could help find problems faster and at a time when they could be easier to treat, Diamond explained.
Meanwhile, the FDA is supporting the development of AI by taking on initiatives to standardize its data, according to Dr. Gregory Pappas, the associate director of national device surveillance at the CDRH.
Diamond also said the FDA is currency developing new regulatory frameworks to better use real-world performance data.
By monitoring real-world performance, the FDA is able to deliver a more robust total product lifecycle-based oversight of medical devices.
The agency’s recent action plan for software as a medical device outlines a multi-pronged approach to AI and ML-based medical software oversight. The plan includes advancing real-world performance pilots and developing other regulatory efforts around AI algorithms.
Category: Federal Civilian
Tags: artificial intelligence FDA federal civilian Food and Drug Administration GI Genius GovernmentCIO Gregory Pappas machine learning Matthew Diamond software as a medical device