Home Business Healthcare AI Predicts Cardiovascular Ris...

AI Predicts Cardiovascular Risk by Analyzing Heart’s Biological Age

Healthcare

Business Honor
02 April, 2025

AI-powered algorithm from Inha University Hospital predicts cardiovascular risk through biological heart age assessment.

A groundbreaking study by researchers at Inha University Hospital in South Korea has uncovered a new AI-based algorithm founded on electrocardiograph (ECG) data to predict cardiovascular risk and cardiac death. The researchers compared ECG information in almost half a million cases and developed an algorithm that could pick out patients at risk by forecasting the biological age of the heart—derived from its functioning rather than their age.

The algorithm functions by matching the biological heart age against an individual's real age. For instance, a 50-year-old with a poor heart condition could have a biological heart age of 60, whereas one with excellent heart health could have a biological heart age of 40. The study found that when the biological heart age is seven years above the chronological age, the risk of death and major cardiovascular events (MACE) increases steeply, as found by Associate Professor Yong-Soo Baek.

On the other hand, when biological heart age is seven years lower than chronological age, the risk of MACE and mortality becomes considerably lower. The study highlights the power of AI for revolutionizing cardiovascular risk stratification and clinical diagnosis. It was revealed that a heart age predicted by AI that is more than seven years ahead of chronological age raises the risk of all-cause mortality by 62% and MACE by 92%. In contrast, a seven-year-old heart lowers the risk of mortality by 14% and MACE by 27%.

The research, based on a deep learning network that was trained on more than 425,000 ECGs, is one towards incorporating AI into medicine to make it possible to more accurately and individualized assess cardiovascular risk. Results were given at the European Society of Cardiology's EHRA 2025 congress in Vienna, where AI was reported to be the key to making it possible for patient care and optimal clinical assessment.