Project Talia - AI for Improved Mental Health

Overview
Groups

One in four of us, at some point in our lives, will be affected by a mental health condition. Good mental health and well-being are fundamental to our general health and quality of life. It enables us to build resilience against everyday stresses, to work productively, to have fulfilling relationships, and to experience life as meaningful. Mental health presents one of the most challenging and under-investigated domains of machine learning research. In Project Talia we are exploring how we can best leverage AI to help improve the effectiveness of important mental health services.

Collaboration with SilverCloud Health

In this project, we are collaborating with SilverCloud Health, the leading digital therapeutics platform for mental and behavioral health. This partnership aims to jointly explore how AI can be used to enhance SilverCloud Health’s digital mental health services that deliver cognitive-behavioral treatment (CBT) programs to a large and growing number of people in need of effective care. Using probabilistic machine learning frameworks, the aim is to identify new routes for personalizing treatments and improving patient engagement and clinical outcomes.

More Effective Digital Mental Healthcare with AI

For improving mental health through AI, our research focuses on the following strategies:

	Stratify Understand patient sub-types which respond best to treatment + interventions
	Personalize Tailor content and delivery to achieve optimal therapy outcomes for individual patients
	Predict Identify which patients are more likely to drop-out for earlier intervention, or different programs
	Intervene Intervene timely to ensure earlier intervention and improved outcomes
	Improve Identify successful patterns in supporter behaviour in relation to patient sub-type to improve therapy effectiveness