AI used to create inexpensive heart disease detector

Washington: Applying artificial intelligence (AI) to a widely available, inexpensive test -- the electrocardiogram (EKG) -- results in a simple, affordable early indicator of a precursor to heart failure, scientists say.

The test accuracy of the AI/EKG system compares favourably with other common screening tests, such as mammography for breast cancer, according to the research published in the journal Nature Medicine. Asymptomatic left ventricular dysfunction is characterised by the presence of a weak heart pump with a risk of overt heart failure, said researchers from Mayo Clinic in the US. It is associated with reduced quality of life and longevity. However, the disorder is treatable when identified. There is no inexpensive, noninvasive, painless screening tool for asymptomatic left ventricular dysfunction available for diagnostic use, researchers said.

The study found that the best existing screening test for asymptomatic left ventricular dysfunction is to measure natriuretic peptide levels (BNP), but results of BNP have been disappointing. The test also requires blood draws. Left ventricular dysfunction typically is diagnosed with expensive and less accessible imaging tests, such as echocardiograms, or CT or MRI scans. "Congestive heart failure afflicts more than 5 million people and consumes more than USD 30 billion in health care expenditures in the US alone," said Paul Friedman from Mayo Clinic. "The ability to acquire an 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," he said.

The researchers hypothesised that asymptomatic left ventricular dysfunction could be reliably detected in the EKG by a properly trained neural network. Using stored digital data, 625,326 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 favourably with other common screening tests, such as prostate-specific antigen for prostate cancer, mammography for breast cancer and cervical cytology for cervical cancer. 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 Friedman.