We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress
Sign In
Advertise with Us

Download Mobile App


ATTENTION: Due to the COVID-19 PANDEMIC, many events are being rescheduled for a later date, converted into virtual venues, or altogether cancelled. Please check with the event organizer or website prior to planning for any forthcoming event.
16 Feb 2023 - 18 Feb 2023

FDA to Establish Oversight Rules for AI in Medicine

By HospiMedica International staff writers
Posted on 17 Apr 2019
Print article
The US Food and Drug Administration (FDA; Silver Spring, MD, USA) is developing a framework for regulating artificial intelligence (AI) products used in medicine that continually adapt based on new data.

In a white paper published in March 2019, the FDA details the criteria the agency proposes for rules that will be used to determine when and if medical products that rely on AI will require FDA review before being commercialized. The FDA review may include examination of the underlying performance of a product’s algorithms, a manufacturer’s plan to make modifications, and the manufacturer’s ability to manage the risks associated with any modifications.

The FDA has already approved medical devices that rely on “locked algorithms,” which do not change each time they are used, but instead are changed by a manufacturer at intervals, using specific training data and a validation process to ensure proper functioning of the system. Among such devices approved during 2018 were a device that is used to detect degenerative diabetic retinopathy, and another one designed to alert providers of a potential stroke in patients.

According to the FDA, the proper performance of those locked algorithms, and others like them, is crucial to ensuring that doctors base life-and-death treatment decisions on accurate information. That task is harder for products that learn and evolve on their own, in ways that are difficult even for the manufacturers of such systems to understand. An example of such one system uses AI algorithms to identify breast cancer lesions on mammograms and learns to improve its confidence and identify new subgroups of cancer, based on its exposure to additional real world data.

“A new approach to these technologies would address the need for the algorithms to learn and adapt when used in the real world. It would be a more tailored fit than our existing regulatory paradigm for software as a medical device,” explained FDA outgoing commissioner Scott Gottlieb, MD. “I can envision a world where, one day, artificial intelligence can help detect and treat challenging health problems, for example by recognizing the signs of disease well in advance of what we can do today.”

The FDA recently launched a fellowship program with Harvard University (Boston, MA, USA) on AI and machine learning, which is focused on designing, developing, and implementing algorithms for regulatory science applications. One such example is innovative clinical decision support software that uses AI algorithms to help alert neurovascular specialists of brain deterioration.

Related Links:
US Food and Drug Administration

Gold Supplier
Premium Ultrasound Scanner
Memory Foam Mattress
Analgesic Gas Delivery System
O-Two Equinox Advantage
X-Ray Image Acquisition Software
dicomPACS DX-R

Print article



view channel
Image: A novel research study moves the needle on predicting coronary artery disease (Photo courtesy of Pexels)

AI-Enabled ECG Analysis Predicts Heart Attack Risk Nearly as well as CT Scans

Increased coronary artery calcium is a marker of coronary artery disease that can lead to a heart attack. Traditionally, CT scans are used to diagnose buildup of coronary artery calcium, although CT scanners... Read more

Critical Care

view channel
Image: The advanced electronic skin could enable multiplex healthcare monitoring (Photo courtesy of Terasaki Institute)

First-of-Its-Kind Electronic Skin Patch Enables Advanced Health Care Monitoring

For some time now, electronic skin (E-skin) patches have been used to monitor bodily physiological and chemical indicators of health. Such monitors, placed on the skin, are capable of measuring various... Read more

Surgical Techniques

view channel
Image: The neuro-chip with soft implantable electrodes could manage brain disorders (Photo courtesy of EPFL)

Implantable Neuro-Chip Uses Machine Learning Algorithm to Detect and Treat Neurological Disorders

Using a combination of low-power chip design, machine learning algorithms, and soft implantable electrodes, researchers have produced a neural interface that can identify and suppress symptoms of different... Read more

Point of Care

view channel
Image: Steripath improves the diagnostic accuracy and timeliness of sepsis test results (Photo courtesy of Magnolia)

All-in-One Device Reduces False-Positive Diagnostic Test Results for Bloodstream Infections

Blood cultures are considered the gold standard diagnostic test for the detection of blood stream infections, such as sepsis. However, positive blood culture results can be frequently wrong, and about... Read more


view channel
Image: Researchers expect broader adoption of AI in healthcare in the near future (Photo courtesy of Pexels)

Artificial Intelligence (AI) Could Save U.S. Healthcare Industry USD 360 Billion Annually

The wider adoption of artificial intelligence (AI) in healthcare could save the U.S. up to USD 360 billion annually although its uptake in the industry is presently limited owing to the absence of trust... Read more
Copyright © 2000-2023 Globetech Media. All rights reserved.