About the Project

This project explored how artificial intelligence can help identify individuals at risk of anxiety, depression, and stress following large-scale public health emergencies such as the COVID-19 pandemic. Using data from more than 9,000 participants in Catalonia, we developed machine learning models capable of detecting mental health vulnerability patterns and stratifying populations into meaningful risk profiles.

Beyond prediction, the project focused on explainable AI techniques to better understand the factors driving mental health outcomes, including social support, sleep changes, physical activity, and previous health conditions. By combining predictive modeling with interpretable visual analytics, the study aimed to support early intervention strategies and improve preparedness for future public health crises.

The work was carried out in collaboration with leading research institutions in Catalonia, including Barcelona Institute for Global Health and Germans Trias i Pujol Research Institute.