Mood state and outcome prediction in mood disorders using digital phenotyping andmachine learning

Individuals with mood disorders suffer with a significant burden. Beside experiencing mood symptoms, they also have cognitive and functioning impairments, are at greater risk of suicide and hospitalization, and have a poorer quality of life. Traditional psychiatric assessments are subjective and not able to capture events in real-time. Smartphone assessments and digital phenotyping – the interaction between user and smartphone captured in real-time – can provide a more robust, objective, and extensive view of what is going on with mood disorder subjects. We intend to use the mettleAI app to capture clinical assessments and passively collect data to predict mood episodes, outcomes, and to improve the user experience with the platform. The intern will be able to apply his research in a business context, translating his academic experience into an applicable tool. The partner organization will be able to perfect their product and deliver to the market a state-of-the-art application enriched by clinical research and users’ feedback.

Intern: 
Diego Librenza Garcia
Faculty Supervisor: 
Benicio Frey
Province: 
Ontario
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