Digital Tools for Mental Health
The project MoodifAI includes the following two subprojects:
Diagnosis and monitoring of mental health still rely on self-reported symptoms during clinical visits, and thus, assessing patients’ daily status and changes is a challenge. Our vision is to combine digital tools to collect daily multi-modal data and Machine Learning and move towards precision mental health care by providing differential diagnosis and individualized treatment recommendations.
Contact
Dr. Giulia da Poian
Depression is the leading cause of disability in the world. Many efforts have been made to identify markers representative of treatment response, but treating mental health remains a trial-and-error approach. The proliferation of mobile devices and wearable sensors for behavioral and physiological monitoring could help address these challenges. Our main objectives are to identify digital biomarkers for unobtrusive and continuous characterization of the course of depression, develop methods for modelling response to therapy, and understand to what extent we can improve outcomes by using closed-loop personalized treatments.