Dr. Belgrave's research focuses on integrating medical domain knowledge to develop statistical machine learning models to understand disease progression. Dr. Belgrave's main research interests are in probabilistic modelling to develop personalized treatment strategies in health.

Machine learning advances are opening new routes to more precise healthcare, from the discovery of disease subtypes for stratified interventions to the development of personalised interactions supporting self-care between clinic visits. As medicine pivots from treating diagnoses to treating mechanisms the need for more intelligent phenotyping and frequent interaction brings machine learning and AI into the spotlight. This offers an exciting opportunity for machine learning techniques to impact healthcare in a meaningful way. In this talk, we will look at some of the key challenges in machine learning for healthcare and some of the advances which have been made towards addressing these challenges. I will also focus on how probabilistic models can enable us to develop a more personalised approach to healthcare whereby information can be aggregated from multiple sources within a unified modelling framework. The work presented will be motivated within specific clinical contexts.