Mental Health Identification System

Abstract

In an era where technology's reach extends to the intricacies of human well- being, "Mental Health Identification" emerges as a thought-provoking narrative that explores the convergence of innovation, ethics, and mental health. Relationships strain under the weight of newfound possibilities, underscoring. Developing an AI-Enabled Mental Health Identification for Early Intervention This project introduces an innovative AI-enabled mental health identification designed to revolutionize the early identification of mental health conditions. The project’s goal is to create a valuable tool that contributes to improved mental health awareness and support. The abstract provides a concise overview of the project. It highlights the development of an artificial intelligence-based mental health identification that utilizes cutting- edge machine learning algorithms to analyze face patterns, facial expressions, and textual inputs. The project’s focus is on creating an automated and non-intrusive tool for early detection and assessment of mental health conditions, aiming to contribute to improved mental health awareness and support. Mental health disorders have become one of the leading causes of disability worldwide, affecting millions of individuals. The early identification of mental health conditions is crucial for effective treatment and prevention. This paper presents a Mental Health Identification System that utilizes machine learning algorithms to predict and identify common mental health disorders based on a questionnaire dataset. The model is designed to focus on anxiety, depression, and stress disorders, using classification techniques to analyze user inputs