New AI algorithm to predict risk of cardiovascular events, heart-related death

A team of researchers in South Korea has developed a novel artificial intelligence AIbased algorithm that uses electrocardiograph ECG2 data to predict the risk of cardiovascular events and heartrelated deathTo create the algorithm the team from Inha University Hospital analysed standard 12lead electrocardiograph ECG2 data taken from almost half a million casesThe novel algorithm can identify people most at risk of cardiovascular events and mortality by predicting the biological age of the heart which is based on how the heart functionsFor example a person who is 50 but has poor heart health could have a biological heart age of 60 while someone aged 50 with optimal heart health could have a biological heart age of 40ldquoOur research showed that when the biological age of the heart exceeded its chronological age by seven years the risk of allcause mortality and major adverse cardiovascular events increased sharplyrdquo said YongSoo Baek Associate Professor at Inha University HospitalldquoConversely if the algorithm estimated the biological heart as seven years younger than the chronological age that reduced the risk of death and major adverse cardiovascular eventsrdquo Baek addedThe study showed that the integration of AI into clinical diagnostics presents novel opportunities for enhancing predictive accuracy in cardiologyldquoUsing AI to develop algorithms in this way introduces a potential paradigm shift in cardiovascular risk assessmentrdquo said BaekFor the study the team developed a deep neural network and trained on a substantial dataset of 425051 on 12lead ECGs collected over fifteen years It was subsequently validated and tested on an independent cohort of 97058 ECGsIn statistical models an AI ECGheart age exceeding the heartrsquos chronological age by seven years was associated with an increased risk of allcause mortality by 62 per cent and of MACE by 92 per centIn contrast an AI ECG heart age that was seven years younger than its chronological age reduced the risk of allcause mortality by 14 per cent and MACE by 27 per centMACE is Major Adverse Cardiovascular Events and includes heart attack stroke Cardiovascular death and revascularisation procedures such as angioplasty and bypass surgeryldquoThis study confirms the transformative potential of AI in refining clinical assessments and improving patient outcomesrdquo said BaekThe study was presented at the ongoing EHRA 2025 a scientific congress of the European Society of Cardiology ESC in Vienna AustriaThis story has been sourced from a third party syndicated feed agencies Midday accepts no responsibility or liability for its dependability trustworthiness reliability and data of the text Midday managementmiddaycom reserves the sole right to alter delete or remove without notice the content in its absolute discretion for any reason whatsoever