Data science to tackle cardiovascular conditions
The war on cardiovascular disease is being bolstered by the appliance of data science with the British Heart Foundation and The Alan Turing Institute awarding £550,000 worth of funding to six projects which aim to transform diagnosis and treatment of circulatory conditions.
The six projects include developing a risk predictor tool, which will aim to anticipate the risk of heart attacks; using machine learning to personalise the risk posed by factors such as smoking and high blood pressure; and analysing images of blood cells from 30,000 healthy people to identify genetic factors that could lead to heart attacks or strokes.
The studies form part of The Alan Turing Institute’s health research programme, which aims to improve the scientific understanding of disease and boost health through data-driven innovation in AI and data science.
The Alan Turing Institute programme director for health Professor Chris Holmes said: “The application of data science research methods has the potential to revolutionise the way cardiovascular disease is diagnosed and treated. We know that heart and circulatory disease is the biggest killer in the UK, so the impact of this work is not only far-reaching but could potentially save lives.”
BHF associate medical director Metin Avkiran added: “The UK is blessed with many world-class heart and circulatory disease researchers, spanning a wide range of disciplines.
“But, as we enter the era of digital medicine, there’s a growing need to foster excellence in applying data science solutions to cardiovascular problems. At the BHF, we recognise the enormous potential of data science and want to create an environment where we can realise that potential.
“This funding is a major step towards using data science to make transformational improvements in preventing, detecting and treating heart attacks and strokes, as well as other heart and circulatory diseases.”