Artificial Intelligence and Bipolar Disorder

An artificial intelligence solution to predict and prevent clinical relapse in bipolar disorder using smartphone electronic biomarkers.

This project is developing a novel artificial intelligence solution to predict and prevent clinical relapse in bipolar disorder using smartphone electronic biomarkers.

Bipolar affective disorder (BPAD) is a sever and chronic mental illness characterised by episodes of mania (feeling extremely elated, and energetic, with associated self-destructive behaviour) and depression (feeling low in mood, easily tired, and lacking interest). Lifetime prevalence of BPAD is around 3.5% and mortality due to suicide around 60%. Early recognition of relapse signatures is exceptionally difficult leading to delay in treatment and associated harms.

This project seeks to develop a platform for people with BPAD that uses electronic markers to generate a probability statistic of onset of a manic or depressive episode. The technology will securely alert a treating psychiatrist if a diagnostic threshold is triggered to enable early intervention.

Currently well patients and their psychiatrists will initiate he use of this technology through an informed consent process as part of an advance care directive.

Research Team

Funding

Seed Funding 2017