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Project Talia – AI for Improved Mental Health

Work on Project Talia has now been retired. We continue to actively explore the healthcare and AI space, with other projects within Microsoft Health Futures (opens in new tab).

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 (opens in new tab)

In this project, we are collaborating with SilverCloud Health (opens in new tab), 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




Microsoft Research

Portrait of Junaid Bajwa

Junaid Bajwa

Chief Medical Scientist

Portrait of Hannah Richardson (nee Murfet)

Hannah Richardson (nee Murfet)

Senior Compliance Manager

Portrait of Aditya Nori

Aditya Nori

Partner Research Manager

Portrait of Niranjani Prasad

Niranjani Prasad

Senior Researcher

Portrait of Anja Thieme

Anja Thieme

Principal Researcher

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