ZENMIND: A Machine Learning Powered Depression Diagnosis and Treatment Recommendation System

Depression, a prevalent mental health condition, significantly impacts individuals' well-being and quality of life. Early and accurate detection is crucial for effective intervention, yet many individuals struggle to recognize their symptoms or seek timely help. To address this challenge, we developed ZENMIND an AI-powered system that utilizes machine learning and Generative AI (GenAI) to assist in depression detection and personalized treatment recommendations. The system employs a questionnaire-based assessment, inspired by standardized tools such as the PHQ-9 and BDI, to systematically evaluate users' symptoms, emotional state, and behavioral patterns. By leveraging advanced machine learning algorithms, the platform analyzes quiz responses to provide a personalized depression risk assessment, encouraging individuals to seek professional support when needed. Beyond detection, the solution integrates GenAI to generate tailored wellness recommendations, including customized workout routines, dietary suggestions, and self-care strategies aligned with the user's mental health profile. Additionally, it features an AI-powered conversational agent, offering empathetic guidance, mental health education, and continuous emotional support. Users also gain access to a curated library of reliable information on depression, treatment options, and a directory of mental health organizations. By combining scientifically validated assessments with AI -driven insights, the system aims to bridge the gap between self-assessment and professional care, fostering early intervention, personalized well-being strategies, and improved mental health outcomes.