AI algorithm can predict chances of death from heart attack more accurately than human doctors

Artificial intelligence at a US health centre can predict a person’s chances of dying from heart test results, including those that look normal to doctors, but how it works remains a mystery.

Algorithms developed by researchers at the health care provider Geisinger in Pennsylvania can calculate a patient’s survival rate within a year by analysing echocardiogram (ECG) results, according to an article published by New Scientist earlier this month.

The AI examined 1.77 million ECG results from 400,000 patients before concluding whether the patients would survive for the next year. Researchers trained the algorithm using two models. One was based on raw historical ECG data, measuring voltage over time, while the other was fed the ECG data in combination with the age and sex of the patients.

When comparing the two groups of patients, those that died within a year and those that survived, the AI scored above 0.85, where 1.0 was a perfect score, while traditional methods by doctors scored between 0.65 and 0.8.

“No matter what, the voltage-based model was always better than any model you could build out of things that we already measure from an ECG,” Brandon Fornwalt of Geisinger told New Scientist. 

A parallel algorithm used traditional readings of ECGs that doctors would use to detect conditions such as heart attacks and atrial fibrillation.