Project Talia – AI for Improved Mental Health

Project Talia – AI for Improved Mental Health


Microsoft Research blog

Microsoft Research blog


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:

Search icon Stratify
Understand patient sub-types which respond best to treatment + interventions
Icon of a figure within right-circling arrows Personalize
Tailor content and delivery to achieve optimal therapy outcomes for individual patients
Icon of basic shapes extending out of a cloud Predict
Identify which patients are more likely to drop-out for earlier intervention, or different programs
Icon with two figures connected by arrows Intervene
Intervene timely to ensure earlier intervention and improved outcomes
Icon of a figure with right-circling arrows Improve
Identify successful patterns in supporter behaviour in relation to patient sub-type to improve therapy effectiveness


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Silvercloud Collaborators

  • Portrait of James Bligh

    James Bligh

    CTO SilverCloud

  • Portrait of Gavin Doherty

    Gavin Doherty

    UX Director

  • Portrait of Angel Enrique

    Angel Enrique

    Clinical Researcher

  • Portrait of Dessie Keegan

    Dessie Keegan

    Software Developer Engineer

  • Portrait of Jorge Palacios

    Jorge Palacios

    Clinical Researcher

  • Portrait of Derek Richards

    Derek Richards

    Chief Science Officer