Machine learning for personalised mental healthcare: a human-centred approach

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. This offers an exciting opportunity for machine learning techniques to impact healthcare in a meaningful way. Within the healthcare domain, machine learning for mental healthcare is an under-investigated area and yet a potentially highly impactful area of research. In this talk, I will present recent work on probabilistic graphical modelling to enable a more
personalised approach to mental healthcare, whereby information can be aggregated from multiple sources within a unified modelling framework. We present a human-centred approach to mental healthcare which is aimed at increasing the effectiveness of psychological wellbeing practitioners.