😔 😞 😣 😖 😩 Detect depression on social media using the ssToT method introduced in our ASONAM 2017 paper titled "Semi-Supervised Approach to Monitoring Clinical Depressive Symptoms in Social Media"
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Updated
Feb 26, 2019 - Jupyter Notebook
😔 😞 😣 😖 😩 Detect depression on social media using the ssToT method introduced in our ASONAM 2017 paper titled "Semi-Supervised Approach to Monitoring Clinical Depressive Symptoms in Social Media"
MentalChecker est une application web d'auto-évaluation de la santé mentale utilisant les échelles standardisées PHQ-9 et GAD-7. Conçue pour offrir un espace confidentiel et humain, elle oriente également les utilisateurs vers des ressources de soutien locales au Burkina Faso. Bâti avec React, TypeScript et Tailwind CSS.
PHQ-9 depression score prediction with interactive clinician dashboard - portfolio ML demo built on public dataset.
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Mental health support platform with PHQ-9/GAD-7 assessments, AI analysis, and 24/7 WhatsApp chatbot. HIPAA-compliant design with crisis detection.
AI-based mental health risk assessment system using PHQ-9, machine learning, sentiment analysis, and trend monitoring.
AI-powered clinical documentation tool - conversational PHQ-9/GAD-7 screenings and structured DAP/SOAP/BIRP note generation from therapy transcripts
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