As technology in medicine continues to grow by leaps and bounds, the onus on incorporating it in a manner that benefits both patients and physicians has never been greater. A recent study into use of artificial intelligence (AI) to predict overall health using 12-lead ECG readings is one of many examples in cardiology where physicians are looking to do just that. Suraj Kapa, MD, cardiac electrophysiologist at the Mayo Clinic in Minnesota, was the lead investigator of that study and he is the subject of this episode of the DocTalk Podcast. I'm Patrick Campbell, associate editor with MD Magazine, and I will be your host for this edition of DocTalk as we discuss using AI to determine overall physical health from 12-lead ECG readings with Dr. Kapa. Welcome to DocTalk, Dr. Kapa, if you wouldn't mind introducing yourself to our audience and telling us a little bit about your background, and listing any relevant disclosures you have before we begin, then we can dive into our chat.

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.

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.

In the not-too-distant future, medical professionals might be able to apply AI to electrocardiogram data in order to measure a patient's overall health status. This is according to new research published in Circulation: Arrhythmia and Electrophysiology, a journal of the American Heart Association. An electrocardiogram - also called an EKG or ECG - is a test used to measure the electrical activity of the heart. A patient's sex and age can have an effect on how an EKG turns out. That's why the team of researchers built an AI that could determine a patient's gender and estimate their'physiologic age' - an indicator of overall health that is different from chronological age.

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.