In an era marked by an abundance of options in the health IT marketplace, Mayo Clinic Platform aims to get proven tools to healthcare providers.

Medical innovations don’t happen overnight — but in today’s digital world, they happen pretty fast. Some are advancing faster than you think.

Rochester, Minn.-based Mayo Clinic has named the eight founding members of a global data-sharing network that aims to tailor medical care with artificial intelligence.

Rochester, Minn.-based Mayo Clinic Platform is helping bring digital health tools to market by launching Solutions Studios. 

Best practices for integrating AI into your technology infrastructure.

At HIMSS24, the president of Mayo Clinic Platform offered some tough truths about the challenges of deploying genAI – touting its enormous potential while spotlighting patient safety dangers to guard against in provider settings.

At one of health technology’s biggest events, the conversation around artificial intelligence has changed.

Mayo Clinic's Dr. Sonya Makhni answers key questions on creating and delivering artificial intelligence, inherent bias and the importance of risk classification systems.

This year's J.P. Morgan Healthcare Conference brought a bevy of news announcements — from acquisitions to partnerships to new products and more. This list compiles short summaries for seven of the event’s most notable announcements.

Rochester, Minn.-based Mayo Clinic's 2030 strategy is simple: to cure, connect and transform. But to get there, the world-renowned health system needs a robust people strategy developing the workforce of the future.

Rochester, Minn.-based Mayo Clinic is using an artificial intelligence algorithm to identify a left ventricular cardiovascular disease that can go unnoticed until a serious cardiac event, the Post Bulletin reported Nov. 2.

At HLTH, Mayo Clinic Platform President John Halamka gave a window into how his health system is mitigating generative AI risks. Some of the measures Mayo is taking include running analyses on how well algorithms perform across various subgroups and training models only on internal de-identified data.