Cutting-Edge Mental Health Evaluation and Tracking System

Cutting-Edge Mental Health Evaluation and Tracking System

Mr. Syed Abdul Khaliq1, A Vara Prasad2, D Ajay Kumar3, M Sai Charan Reddy4, R Sriharsha5
1 Assistant Professor of Department of AI&ML, J.B. Institute of Engineering and Technology, Hyderabad

2 Department of AI&ML, J.B. Institute of Engineering and Technology, Hyderabad

3 Department of AI&ML, J.B. Institute of Engineering and Technology, Hyderabad

4 Department of AI&ML, J.B. Institute of Engineering and Technology, Hyderabad

5 Department of AI&ML, J.B. Institute of Engineering and Technology, Hyderabad

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A Revolutionary Mental Health Assessment and Monitoring System

Abstract:

Mental health disorders are common, and novel solutions for evaluation and tracking of these disorders are being sought. In this work, we describe a deep learning-based framework that incorporates AI-assisted self-assessment tools and real-time mental health monitoring. Using advanced feature extraction techniques and a wide array of machine learning models, we make predictions about mental health trends to enable timely interventions. Data-driven mental health overview will provide an efficient user experience while balancing the professional perception of the individual. This system encompasses predictive analytics, personalized interventions, and real-time tracking mechanisms that work together to enhance mental health support and implement preventive measures against potential crises.

Keywords: Mental Health  AI; Deep Learning; Self-Assessment; Predictive Analytics; Feature Extraction; Crisis Prevention