Artificial Intelligence Helps Detect Early Heart Disease, Mayo Researchers Find

Jan. 10, 2019
A new Mayo Clinic study has found that applying artificial intelligence (AI) to an electrocardiogram (EKG) test results in an easy early indicator of asymptomatic left ventricular dysfunction, which is a precursor to heart failure.

A new Mayo Clinic study has found that applying artificial intelligence (AI) to an electrocardiogram (EKG) test results in an easy early indicator of asymptomatic left ventricular dysfunction, which is a precursor to heart failure.

The Mayo research team found that the AI/EKG test accuracy compares favorably with other common screening tests, such as mammography for breast cancer. The findings were published in the journal Nature Medicine.

Asymptomatic left ventricular dysfunction is characterized by the presence of a weak heart pump with a risk of overt heart failure. It affects 7 million Americans, and is associated with reduced quality of life and longevity. But asymptomatic left ventricular dysfunction is treatable when identified, Mayo researchers explained. But they added that there is currently no inexpensive, noninvasive, painless screening tool for asymptomatic left ventricular dysfunction available for diagnostic use.

In their study, Mayo Clinic researchers hypothesized that asymptomatic left ventricular dysfunction could be reliably detected in the EKG by a properly trained neural network. Using Mayo Clinic stored digital data, more than 625,000 paired EKG and transthoracic echocardiograms were screened to identify the population to be studied for analysis. To test their hypothesis, researchers created, trained, validated and then tested a neural network.

The study concluded that AI applied to a standard EKG reliably detects asymptomatic left ventricular dysfunction. The accuracy of the AI/EKG test compares favorably with other common screening tests, such as prostate-specific antigen for prostate cancer, mammography for breast cancer and cervical cytology for cervical cancer.

“Congestive heart failure afflicts more than 5 million people and consumes more than $30 billion in health care expenditures in the U.S. alone,” said Paul Friedman, M.D., senior author and chair of the Midwest Department of Cardiovascular Medicine at Mayo Clinic. "The ability to acquire a ubiquitous, easily accessible, inexpensive recording in 10 seconds—the EKG—and to digitally process it with AI to extract new information about previously hidden heart disease holds great promise for saving lives and improving health.”

The study also revealed that in patients without ventricular dysfunction, those with a positive AI screen were at four times the risk of developing future ventricular dysfunction, compared with those with a negative screen. “In other words, the test not only identified asymptomatic disease, but also predicted risk of future disease, presumably by identifying very early, subtle EKG changes that occur before heart muscle weakness,” said Dr. Friedman.

Sponsored Recommendations

How Digital Co-Pilots for patients help navigate care journeys to lower costs, increase profits, and improve patient outcomes

Discover how digital care journey platforms act as 'co-pilots' for patients, improving outcomes and reducing costs, while boosting profitability and patient satisfaction in this...

5 Strategies to Enhance Population Health with the ACG System

Explore five key ACG System features designed to amplify your population health program. Learn how to apply insights for targeted, effective care, improve overall health outcomes...

A 4-step plan for denial prevention

Denial prevention is a top priority in today’s revenue cycle. It’s also one area where most organizations fall behind. The good news? The technology and tactics to prevent denials...

Healthcare Industry Predictions 2024 and Beyond

The next five years are all about mastering generative AI — is the healthcare industry ready?