Mental Health Survey Classifier

This is a student-made web application that predicts potential signs of depression or anxiety based on survey responses. The model uses logistic regression and is integrated into a Flask web app.

🚀 Features

• Custom-built logistic regression (no sklearn)
• Survey based on PHQ-9 (subset)
• User authentication with roles (user/admin)
• Admin dashboard to view/delete users
• Predictions based on survey inputs

📦 Tech Stack

• Python + Flask
• Flask-WTF, Flask-Login, Flask-Mail, Flask-Migrate
• Bootstrap 5 for styling
• pyodbc for MSSQL connection
• NumPy, joblib (for model handling)

📋 Requirements

Install dependencies:

pip install -r requirements.txt

🛠️ Setup Instructions

1. Clone the repo:

git clone https://github.com/codingburgas/2425-11-b-pp-student-practices-assignment-ZBDinev21.git
cd 2425-11-b-pp-student-practices-assignment-ZBDinev21

2. Edit the config.py with your DB credentials.
3. Run the app:

python run.py

🧠 AI Model

The logistic regression is implemented manually and trained using PHQ-9-style numeric data. It returns binary predictions (1 = likely symptoms, 0 = low symptoms).

🧪 Testing

Basic unit tests are in tests/. To run:

python -m unittest discover tests/

📈 Roles

• User: can take the survey, view results
• Admin: can manage users, view database entries

📬 Email Confirmation

Flask-Mail + itsdangerous is used for user registration confirmation (optional).

📄 License

Student Project – Not for commercial or clinical use.