ECG using AI can be affordable and helpful for detecting early heart condition, says study

Heart problem
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Researchers found that applying Artificial Intelligence (AI) to a widely available inexpensive test can help to detect heart condition that could trigger heart failure.

Researchers from Minnesota's Mayo Clinic stated in a new study that using AI with the electrocardiogram (ECG) will be an affordable early indicator of asymptomatic left ventricular dysfunction, which is typically diagnosed with expensive tests, such as echocardiograms, MRI or CT scans.

Patients with abnormalities of left ventricular (LV) systolic or diastolic function are not rare, but in many cases, they never noticed any symptom, especially in early stages. The prevalence of this condition increases in the presence of risk factors such as diabetes, coronary artery disease and hypertension.

However, as per the study, which was published in the journal Nature Medicine, the AI applied to a standard ECG can detect asymptomatic left ventricular dysfunction in early stages.

Mayo Clinic's Paul Friedman stated, "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."

During this study, the research team used data of 625,326 persons and paired ECG and transthoracic echocardiograms.

The accuracy of the AI with ECG test compares with other common tests such as a prostate-specific antigen for prostate cancer, cervical cytology for cervical cancer and mammography for breast cancer.

The findings suggested that the patients without ventricular dysfunction, but with a positive AI screen, were at four times the risk of developing future ventricular dysfunction, in comparison to those with a negative screen.

In addition, Friedman said, "The test not only identified asymptomatic disease but also predicted the risk of future disease, presumably by identifying very early, subtle ECG changes that occur before heart muscle weakness."

Related topics : Artificial intelligence