
The motivation for this project stems from the observation that many children experience anxiety due to bullying, classroom trauma, academic pressure, or social challenges, yet these symptoms often go unnoticed until they become severe. The platform combines behavioral questionnaires, emotional assessments, classroom observations, and parental feedback to generate a comprehensive anxiety profile for each child. Machine learning models analyze multiple behavioral and emotional indicators to estimate anxiety risk levels, while Large Language Models (LLMs) provide personalized explanations and evidence-based recommendations tailored to parents, teachers, school counselors, and psychologists.
13 Jul 2026