| Title: | Machine learning discovery of genotype-phenotype associations in cardiovascular science. |
| Lead Institution: | Imperial College London |
| Principal investigator: | Professor Declan O'Regan |
Application 40616
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About
Inherited heart conditions can affect people of any age and may be life-threatening. For many families the first sign that there is a problem is when someone dies suddenly with no obvious explanation. The cause is a mutation or fault in one or more genes inherited from a parent. It is now recognised that up to 600,000 people in the UK carry one of these faulty genes but we know very little about how this affects the heart or what to do about it. Artificial intelligence uses computers to interpret very complex information and could be the key to understanding how inherited heart disease develops. We will use innovative technology to create a three dimensional model of the heart, obtained from scans in thousands of people, to discover how genetic differences start the transition from health to disease, and what treatments could prove successful.5 Publications
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 10071 | APOEε4 carriage associates with improved myocardial performance from adolescence to older age | Constantin-Cristian Topriceanu (+12) | 2024 | BMC Cardiovascular Disorders |
| 9197 | DeepMesh: Mesh-Based Cardiac Motion Tracking Using Deep Learning | Qingjie Meng (+3) | 2024 | IEEE Transactions on Medical Imaging |
| 9732 | Environmental and genetic predictors of human cardiovascular ageing | Mit Shah (+17) | 2023 | Nature Communications |
| 11407 | Identification of an increased lifetime risk of major adverse cardiovascular events in UK Biobank participants with scoliosis | Valentina Quintero Santofimio (+4) | 2023 | Open Heart |
| 10415 | MulViMotion: Shape-Aware 3D Myocardial Motion Tracking From Multi-View Cardiac MRI | Qingjie Meng (+6) | 2022 | IEEE Transactions on Medical Imaging |
Enabling scientific discoveries that improve human health