This research project focuses on developing a new approach to predict and understand heart disease, which is the major cause of death globally. Heart disease is caused by a combination of environmental and genetic factors. Currently, genetic tests are used to estimate if someone might get heart disease, but these tests are invasive and costly. We aim to create methods based on artificial intelligence (AI) that will study medical heart images, and find features in the images that link to specific genes related to heart disease.
We aim to use images of the heart taken during routine medical check-ups (including MRIs) to learn more about the genes that contribute to the development of heart disease. Our plan is to use a method called radiogenomics, which looks at these heart images to find visual patterns, such as different shapes and textures, that could indicate which genes might be involved in causing heart disease. The AI that we will develop will analyse these images and find features that could act as a substitute for genetic tests.
By doing this, we aim to develop a way to predict an individual’s risk of heart disease by studying images of their heart. This would make predicting heart problems easier and more affordable. It could also help us understand more about how genes affect heart health, potentially leading to better ways to prevent and treat heart diseases.
We plan to carry out this project over 18 to 24 months. Ultimately, the outcomes of this project could provide a positive impact on public health by offering a non-invasive, cost-effective method to assess heart disease risk and help doctors make better decisions for their patients.
