Soon, physicians may be able to apply artificial intelligence to electrocardiogram (EKG) data in order to measure overall health status, according to new research published in Circulation: Arrhythmia and Electrophysiology, a journal of the American Heart Association. While it's known that a patient's sex and age could affect an EKG, researchers hypothesized that artificial intelligence could determine a patient's gender and estimate their'physiologic age'--a measure of overall body function and health status distinct from chronological age. Using EKG data of almost 500,000 patients, a type of artificial intelligence known as a convolutional neural network was trained to find similarities among the input and output data. Once trained, the neural network was tested for accuracy on the data of an additional 275,000 patients by predicting the output when only given input data. "While physicians already consider whether a patient'appears [their] stated age' as part of their baseline physical examination, the ability to more objectively and consistently assess this may impact healthcare on multiple levels," says study author Suraj Kapa, MD, assistant professor of medicine and director for Augmented and Virtual Reality Innovation at Mayo Clinic in Rochester, Minn.

An electrocardiogram, also known as an EKG or ECG, is a test used to measure the electrical activity of the heart. While it's known that a patient's sex and age could affect an EKG, researchers hypothesized that artificial intelligence could determine a patient's gender and estimate their'physiologic age' -- a measure of overall body function and health status distinct from chronological age. Using EKG data of almost 500,000 patients, a type of artificial intelligence known as a convolutional neural network was trained to find similarities among the input and output data. Once trained, the neural network was tested for accuracy on the data of an additional 275,000 patients by predicting the output when only given input data. The neural network estimated a patient's chronological age as higher after experiencing adverse health situations such as heart attack, low ejection fraction and coronary artery disease, and lower age if they experienced few or no adverse events.

In the near future, doctors may be able to apply artificial intelligence to electrocardiogram data in order to measure overall health status, according to new research published in Circulation: Arrhythmia and Electrophysiology, a journal of the American Heart Association. An electrocardiogram, also known as an EKG or ECG, is a test used to measure the electrical activity of the heart. While it's known that a patient's sex and age could affect an EKG, researchers hypothesized that artificial intelligence could determine a patient's gender and estimate their'physiologic age'--a measure of overall body function and health status distinct from chronological age. Using EKG data of almost 500,000 patients, a type of artificial intelligence known as a convolutional neural network was trained to find similarities among the input and output data. Once trained, the neural network was tested for accuracy on the data of an additional 275,000 patients by predicting the output when only given input data.