Artificial intelligence could soon be used to predict a patient’s future risk of heart attack or stroke.

A team at the University of Cambridge are developing a machine learning tool that helps predict people’s risk based on their health records, thanks to joint funding from the British Heart Foundation and the Alan Turning Institute.

Researchers plan to use the long-term health records of over two million people in the UK to develop the algorithm.

Currently clinicians and GPs use risk calculators as part of the ‘NHS Health Check’ to asses a patient’s 10-year risk of developing heart or circulatory problems.

But these calculators only take into account a patient’s health at the time it is used, rather than including their medical and family history.

They also don’t account for how a patient’s risk factors have changed over time or differentiate the risk by specific heart and circulatory diseases, such as heart attacks, strokes, heart failure or abnormal heart rhythms.

The algorithm will use a wealth of information on people’s long term health records; map past trends in each patient’s health; and separate and classify the risk for each type of disease.

This will then enable clinicians to better diagnose or predict a patient’s risk of disease and treat them proactively rather than reactively.

Dr Angela Wood, senior university lecturer in biostatistics at The University of Cambridge, said: “It’s only recently that we’ve had the technology to process the huge amount of data available in health records and use it to our own advantage.

“New algorithms could allow us to pick up entirely new and detailed patterns in people’s past health to predict their risk of future events – ultimately saving lives.”

This project is one of six research grant applications awarded through a £550,000 dedicated joint funding scheme between the BHF and The Alan Turing Institute.

The selected projects also include using machine learning to personalise the risk posed by factors such as smoking and high blood pressure to improve the accuracy of intervention and treatment.

The projects will form part of The Turing Institute’s health research programme, which aims to accelerate the scientific understanding of disease and improve health through data-driven innovation in AI and statistical science.

Professor Metin Avkiran, associate medical director at BHF, added: “Investing in data science and machine learning innovation is critical if we want to reduce the burden of early deaths and unnecessarily suffering from heart and circulatory disease.

“Data science is set to accelerate breakthroughs in medical research and the outcome of projects such as this could ultimately transform care for millions of people living under the shadow of heart and circulatory disease in the UK.”

If you want to hear more about what the BHF is up to, chairman, Doug Gurr, is a keynote speaker for Digital Health Rewired in March 2019.

Gurr will be explaining how the medical research charity is now focusing investment in at scale data research in order to achieve a transformational breakthrough in the prediction and prevention of heart disease.

Register your place for Rewired today.