Artificial Intelligence used to make Cheap Heart Disease Detector

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As per a new finding, applying artificial intelligence (AI) to electrocardiogram could be revolutionary. It could serve to be a timely precursor to detect a heart attack. The accuracy of artificial intelligence incorporated electrocardiogram (ECG) endorses its use. It is favorably comparable to other common screening tests such as mammography for breast cancer.

Mayo Clinic Researchers say that asymptomatic left ventricular dysfunction is characteristic of a weak heart pump. It carries a risk of clear heart failure. The condition is a reason for reduced quality of life and reduced life expectancy. However, the condition is treatable when detected.

Applying AI to ECG to bring Sea Change for Heart Diseases

At present, there is no inexpensive, painless, noninvasive screening tool available for diagnosis of asymptomatic left ventricular dysfunction. As stated by the study, the measure of natriuretic peptide levels (BNP) is presently the best one. The test also requires to draw blood.

Typically, left ventricular dysfunction is detected with expensive and less available imaging tests. This includes echocardiograms, MRI, or CT scan.

As stated by an associate at the Mayo Clinic, congestive heart failure affects more than 5 million individuals. The condition causes a burden of more than USD 30 billion to the healthcare system in the U.S. alone.

The incorporation of artificial intelligence to ECG holds great promise for saving lives of individuals. This will add to the advantage of ubiquitous, inexpensive, and easily accessible ECG. The combination works two ways. First it involves recording heart activity using ECG. Secondly, it employs artificial intelligence to bring out new information about previously hidden heart disease. The finding also hypothesized another angle of asymptomatic left ventricular dysfunction.  The condition can be reliably diagnosed using a properly trained neural network.

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