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Diabetes, Obesity and Its Complications
2021-09-02 - 2021-09-03    
All Day
Diabetes Congress 2021 aims to provide a platform to share knowledge, expertise along with unparalleled networking opportunities between a large number of medical and industrial [...]
Heart Ailments
2021-09-07 - 2021-09-08    
All Day
International conference and Expo on Heart Ailments Webinar held at Zoom or WebEx online on September 07-08, 2021. The conference is concentrated on the theme [...]
Computer Graphics & Animation 2021
2021-09-24 - 2021-09-25    
All Day
Computer graphics is branch of Computer Science and Technology It’s a graphical pattern of an image or objects which created by using specific software and [...]
Events on 2021-09-02
Events on 2021-09-07
Heart Ailments
7 Sep 21
Events on 2021-09-24
Latest News

Artificial Intelligence Health Standards and Regulation – CHAI CTA

EMR industry

Race to Define Health AI Standards as Six Groups Step Forward
Government agencies provide minimal guidance on adoption

In recent years, the use of artificial intelligence in health care has grown well beyond reading radiology scans or identifying high-risk sepsis patients. AI is now being used to write medical visit notes, answer patient questions, handle phone calls, and even manage claims. Yet, figuring out which AI tools to adopt, how to implement them effectively, and how to ensure they function safely remains a major challenge for health systems and AI developers. With minimal guidance from government agencies—the FDA oversees only a small portion of these applications—health care organizations often face uncertainty about where to turn.

To fill this gap, several organizations have stepped in to provide guidance, hoping their frameworks will influence the broader industry. These groups range from newly formed collectives to established trade organizations that have been active in health care for decades.

If these organizations achieve widespread adoption, they could shape the standards health systems use to assess and oversee AI technologies, standardize the practices developers follow before releasing health AI products, guide the formation of future regulations, and help prevent adverse effects that might harm patients or hinder industry progress.