In the UK alone, currently, 7 million people live with cardiovascular disease, and this number will increase as the population ages. Under-resourced and under-staffed healthcare systems are struggling with the rising caseload and the large volumes of generated information. Currently, excitement about Artificial Intelligence (AI) for healthcare is high because of its potential to help stem this information overload and reduce healthcare costs.
The AI paradigm fueling this excitement heavily depends on well-curated training data and is primarily seen as a black box. In contrast, we will:
- Learn from complex, multimodal healthcare records with minimal supervision;
- Focus on problems underpinning learning data representations optimised to provide a transparent base for the desired diagnoses and predictions. We will then translate these techniques to automated estimation of cardiac biomarkers, disease diagnosis, and cardiac episode prediction, thus opening roads to preventive care.
