Innovative Web-Based Tool Enhances Teen Mental Health Screening through Biomedical Circuit Analysis and Personalized Recommendations

This study introduces a groundbreaking web-based tool designed to improve the screening of mental health issues in teenagers. Leveraging innovative biomedical circuit analysis techniques and personalized recommendation algorithms, the system provides an advanced approach to early detection and intervention. Through intricate questionnaire modules and specialized Natural Language Processing (NLP) models, user responses are carefully analyzed to offer tailored recommendations. Built with user privacy and accessibility in mind, the application utilizes Flask technology. Calibration of the analysis ensures precise results, marking a significant leap forward in mental health diagnosis. With an impressive accuracy rate of 97%, this tool promises to make a substantial impact on addressing adolescent mental health challenges. Its innovative integration of biomedical circuit analysis and personalized recommendations represents a novel and effective approach to proactive mental health care.