Researchers at Imperial College Healthcare NHS Trust have created an AI model which can flag female patients who are at higher risk of heart disease based on an electrocardiogram (ECG).
The team from Imperial College London and Imperial College Healthcare say that the algorithm, designed for female patients, could enable better treatment and care.
In the British Heart Foundation funded study, published in Lancet Digital Health in March 2025, the researchers used AI to analyse more than one million ECGs from 180,000 patients, of which 98,000 were female.
Researchers developed a score that measures how closely an individual’s ECG matches ‘typical’ patterns of ECGs for men and women, and showed a range of risk for each sex.
Women whose ECGs more closely matched the typical ‘male’ pattern tended to have larger heart chambers and more muscle mass.
These women were also found to have a significantly higher risk of cardiovascular disease, future heart failure, and heart attacks, compared to women with ECGs which more closely match the ‘typical female’ ECG.
Dr Arunashis Sau, academic clinical lecturer at Imperial College London’s National Heart and Lung Institute, and cardiology registrar at the trust, led the research.
He said: “Our work has underlined that cardiovascular disease in females is far more complex than previously thought.
“In the clinic we use tests like ECGs to provide a snapshot of what’s going on but as a result this may involve grouping patients by sex in a way that doesn’t take into account their individual physiology.
“The AI enhanced ECGs give us a more nuanced understanding of female heart health – and we believe this could be used to improve outcomes for women at risk of heart disease.”
Previous evidence had shown that men tend to be at higher risk of cardiovascular disease – which may be due to differences in hormone profiles and lifestyle factors.
This led to a perception among healthcare professionals and the public that women’s risk of cardiovascular disease is low.
However the risk for women is also high, with women twice as likely to die of coronary heart disease, the main cause of heart attack, than from breast cancer in the UK.
Dr Fu Siong Ng, reader in cardiac electrophysiology at the National Heart and Lung Institute at Imperial College London and a consultant cardiologist, said: “Many of the women identified were in fact at even higher risk than the ‘average’ man.
“If it becomes used widely, over time the AI model may reduce gender differences in cardiac care, and improve outcomes for women at risk of heart disease.”
Dr Sonya Babu-Narayan, clinical director at the British Heart Foundation, said: “Harnessing the potential of this type of research could help better identify those patients at highest risk of future heart problems and reduce the gender gap in heart care outcomes.”
In October 2024, the research group published a study in Lancet Digital Health on the AI-ECG risk estimation model, known as AIRE, which can predict patients’ risk of developing and worsening disease from an ECG.