AI-enhanced ECGs may soon assess overall health
An electrocardiogram, also known as an ECG or EKG, is a painless, simple test that records the electrical activity of a person’s heart.
A recent paper in the journal Circulation: Arrhythmia and Electrophysiology, describes how the team developed an artificial intelligence (AI) tool to predict sex and estimate age from ECG data.
The researchers, from the Mayo Clinic College of Medicine and Science, in Rochester, MN, trained the AI tool, which is of a type known as a convolutional neural network (CNN), using ECG readouts from nearly 500,000 individuals.
When they tested the CNN’s accuracy on a further 275,000 people, they found that it was very good at predicting sex but less good at predicting age. The AI tool got the sex right 90% of the time but only got the age right 72% of the time.
The team then focused on 100 people in the test batch for whom they had at least 20 years of ECG readouts.
This closer investigation revealed that the accuracy of the AI tool’s age estimates depended on whether the individuals had experienced heart conditions.
AI has potential to glean ‘physiologic age’
For individuals WHO had practiced heart conditions, the AI tool’s age estimates attended be bigger than their written record ages.
For people who had practiced few or no heart conditions, the AI tool’s age estimates were abundant nearer to the participants’ written record ages.
The results showed that for people that had practiced low ejection fraction, high vital sign, and cardiovascular disease, the AI tool calculable their ages to be a minimum of seven years bigger than their written record ages.
Ejection fraction may be a live of however well the center is pumping.
The researchers say that these results suggest that the tool appears to be estimating biological, or physiologic, age, which, in contrast to chronological age, reflects a person’s overall health status and body function.
“This evidence,” says senior study author Dr. Suraj Kapa, assistant professor of medicine at the Mayo Clinic, “that we might be gleaning some sort of ‘physiologic age’ was certainly both surprising and exciting for [AI’s] 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.”
Physiologic age marker to aid overall health assessment
Even people with no medical training can see that different people appear to age differently.
Scientists investigating aging research are increasingly turning to physiologic age as a way to measure progress of biological aging processes, as opposed to the simple passage of time.
To this end, they have proposed a number of biomarkers, including those that measure substances in the blood, epigenetic alterations to DNA, and the level of frailty.
Dr. Kapa and colleagues recommend that the power to notice discrepancies between age and therefore the age recommended by the heart’s electrical signals may function a helpful biomarker for hidden cardiopathy and alternative conditions.
“Being ready to additional accurately assess overall health standing could facilitate doctors verify that patients they must examine additional to work out if there area unit well or presently silent diseases that would enjoy early identification and intervention,” Dr. Kapa explains.
The analysisers necessitate additional research to validate the employment of the AI-enhanced graphical record as some way to estimate physical age in healthy folks.
The data that they used came from folks that had undergone ECGs for clinical reasons.
“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.”
Dr. Suraj Kapa