Pay attention to the media coverage around artificial intelligence, and it’s easy to get the sense that technologies such as chatbots pose an “existential crisis” to everything from the economy to democracy.

The best use for generative A.I. in health care, doctors say, is to ease the heavy burden of documentation that takes them hours a day and contributes to burnout.

Health care companies are racing to incorporate generative AI tools into their product pipelines and IT systems after the technology displayed an ability to perform many tasks faster, cheaper — and sometimes better — than humans.

As healthcare information exchanges sought to solve EHR interoperability issues, John Halamka, MD, president of the Mayo Clinic Platform, said they haven't worked due to their lack of business model, Computer World reported May 22.

Closing the "evidence gap" to allow providers to deliver more informed care will require better coordination between physicians and data scientists with access to years of patient records, data leaders from Palo Alto, Calif.-based Stanford Health Care and Rochester, Minn.-based Mayo Clinic wrote May 17 in Harvard Business Review.

In dealing with many cases, doctors lack comparative real-time evidence and are forced to make decisions in spite of unknown variables that can dramatically alter outcomes.

Mayo Clinic Platform, the data analytics and digital health arm of the Rochester, Minn.-based medical center, is going global and is expanding its reach to Brazil, Canada and Israel.

Platforms have long been disrupting industries, including healthcare, and are in an unmatched position to solve complex problems endemic to healthcare. For Dr. John Halamka, president of the Mayo Clinic Platform, the drive for platform disruption is personal, and he’s betting big on Mayo Clinic to lead the charge.

As health systems and insurance companies ramp up adoption of artificial intelligence and machine learning technology, experts fear clinical algorithms are not ready for prime time—with potential consequences for patient safety and outcomes.

The research is mounting to show that Anumana’s AI-ECG algorithms could dramatically improve screening for cardiovascular disease (CVD), providing early warnings of disease from just a standard electrocardiogram (ECG).

Mayo Clinic recently welcomed seven more healthcare startups to its accelerator program. In exchange for an equity position in each startup, Mayo Clinic gives young digital health companies the opportunity to refine their AI models using its deidentified data sets and subject matter experts.

We expect that someday many important diagnosis and treatment decisions will be made or augmented by AI applications. Today we are in the early stages of achieving that objective.