ECG has hidden info of overall health status|AI can predict

In coming days Artificial Intelligence can predict your overall health status just by reading your ECG (Electro Cardio Gram), according to a new study.

The latest study was published in Circulation: Arrhythmia and Electrophysiology, a journal of the American Heart Association claim that by applying artificial intelligence to the ECG doctors can predict patient’s overall health.

Researchers already knew that ECG exhibits different report difference in individuals age and whether he is male or female.

They were curious whether it can determine the overall health status or not.

AI is making our health care prediction and diagnosis more accurate. There was recent research in which AI can also predict our mortality by reading the chest X-Ray, not only this, AI-enabled tool can also predict heart attack in advance.

Let us try to find out more about this interesting research and how it’s going to change healthcare science in the near future.

Research methodology

Scientists at US collected data from Myo Clinic digital data vault and identified 774 783 adult patients (18 years or older) with at least one digital ECG acquired between January 1994 and February 2017. For patients with multiple ECGs, only the earliest ECG was selected.

An Artificial Intelligence method was developed known as CNN (Convolutional Neural Network) was trained using ECG signals from 499 727 patients to predict sex and age.

The networks were tested on a separate cohort of 275 056 patients. Subsequently, 100 randomly selected patients with multiple ECGs over the course of decades were identified to assess within-individual accuracy of CNN age estimation.

Results

Of 275 056 patients tested, 52% were males and mean age was 58.6±16.2 years.

For sex classification, the model obtained 90.4% classification accuracy and could determine the chronological age group of a patient with 72% accuracy.

Following are the bullet points of results:

• The AI (convolutional neural networks) is able to identify whether an individual is male or female from an ECG.
• A trained AI can determine an individual’s age from ECG alone within 7 years of their actual age.
• When the AI-predicted age exceeds a patient’s actual age by at least 7 years, there is a higher incidence of cardiovascular comorbidities, potentially suggesting that the AI-predicted age from 12-lead ECGs may correlate with physiological health.

Conclusion

Applying artificial intelligence to the ECG allows prediction of patient sex and estimation of age. The ability of an artificial intelligence algorithm to determine physiological age, with further validation, may serve as a measure of overall health.

Keep reading: How to read ECG: Step-by-step guide

Source:

• Research titled “Age and Sex Estimation Using Artificial Intelligence From Standard 12-Lead ECGs”, published 27 Aug 2019https://doi.org/10.1161/CIRCEP.119.007284Circulation: Arrhythmia and Electrophysiology. 2019