Chronic diseases (e.g. heart disease, cancer and diabetes) and long-term effects of coronavirus disease 2019 (COVID-2019) are worldwide health issues. Technological advances in multi-omics have enabled deeper understanding of disease aetiology as well as more accurate disease prediction, classification and prognosis. Advanced machine learning methods can help to integrate high-dimensional data, such as multi-omics data, to provide meaningful insights into mechanisms underlying disease development and better tools for prediction of disease occurrence and progression. We aim to leverage our techniques in machine intelligence in UK Biobank to:
1) Identify biomarkers that differentiate patient response and disease progression via interpretable models
2) Disentangle molecular pathways underpinning disease mechanisms via genome-wide analyses and causal inference tools
3) Predict and stratify risk of morbidity and mortality in order to achieve better disease prevention and surveillance
Our project will last for 3 years and could potentially deepen our understanding of disease aetiology, provide novel targets for drug discovery, facilitate routine clinical operations by treatment prioritization and improve long-term management of chronic diseases and COVID-19 .