AI model identifies women at risk of heart disease

Designed specifically for female patients, the model could enable doctors to identify high-risk women earlier, thereby enabling better treatment and care. The research was led by Imperial College London and is detailed in The Lancet Digital Health.

In their British Heart Foundation funded study, the researchers used artificial intelligence to analyse over one million ECGs from 180,000 patients, of whom 98,000 were female.

The researchers developed a score that measures how closely an individual's ECG matches ‘typical’ patterns of ECGs for men and women, and which showed a range of risk for each sex. Women whose ECGs more closely matched the typical ‘male’ pattern – such as having an increased size of the electrical signal – 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 more closely matching the ‘typical female’ ECG.