Aug. 27 (UPI) -- Electrocardiogram, or EKG, is already used to help diagnose heart health. But what if they could also give a glimpse into overall health?
Artificial intelligence may be able to use EKG data to determine a person's gender and "physiologic age," a calculation of a person's body function that doesn't factor in actual age, according to a study published Tuesday in the journal Circulation: Arrhythmia and Electrophysiology.
"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," study author Suraj Kapa, a researcher at Mayo Clinic and study author, said in a news release.
The researchers trained an artificial intelligence technology known as a convolution neural network to recognize input and output EKG data for nearly 500,000 patients. The data included a patient's chronological age and whether they had any health ailments.
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Following the training, they tested it the system on another input date from another 275,000 patients. The network pinpointed the patient's gender with 90 percent accuracy and chronological age with 72 percent accuracy.
The neural network closely approximated a higher chronological age for patients who had heart attacks, coronary artery disease or other negative outcomes. It also estimated a lower age if the patients who had few or no adverse health events.
"This evidence -- that we might be gleaning some sort of 'physiologic age' -- was certainly both surprising and exciting for its potential role in future outcomes research, and may foster a new area of science where we seek to better understand the biologic underpinnings of such a finding," Kapa said.
