Machine learning to model disease mechanisms and predict outcomes in cardiomyopathy
A multidisciplinary team of scientists is using the latest technology to help predict how cardiomyopathy will affect individual patients. Cardiomyopathy is a group of diseases affecting the heart muscle, which can lead to heart failure or sudden death. We know that changes in certain genes – known as mutations – increase the risk of developing cardiomyopathy, however, genetic testing alone isn’t enough to tell if or when someone will develop heart problems. It’s possible that artificial intelligence (AI) could help us make better decisions about diagnosis and treatment in cardiomyopathy. AI can do many tasks faster and more accurately than humans. In this BHF-funded study, scientists will come together to harness AI in the analysis of thousands of existing heart scans from current and past patients. It will be trained to recognise the earliest signs of heart damage when preventative treatment may be most useful. It will also combine what it learns from heart scans with information about the mutations carried by each patient. This will give vital insights in the search for new and more effective tools to detect cardiomyopathy at an early stage. This multidisciplinary team hope that in the future, AI will help doctors and cardiomyopathy patients make more informed choices about their treatment, and accelerate the discovery of new treatments.
Project details
| Grant amount | £1,118,463 |
|---|---|
| Grant type | Chairs & Programme Grants |
| Application type | Programme Grant |
| Start Date | 01 January 1900 |
| Duration | 5 years |
| Reference | RG/19/6/34387 |
| Status | In Progress |
