DiagAI - Transforming Health Diagnosis with Intelligent Prediction

A web app designed to assist healthcare practioners with clinical decision making and helps them to make more informed decisions during diagnosis of their patients. This tool allows doctors to input symptoms and relevant patient information, which the AI then analyzes to generate a list of potential illnesses or diseases. The goal of this to help medical doctors make diagnosis decision faster and also aid in making more accurate decisions

• Symptom Analysis: Input patient symptoms to receive accurate illness predictions.
• Data-Driven Insights: It does so by means a model that is trained on medical information peculiar to Nigeria, as well as other verfied medical data from the web for informed decision-making.
• User-Friendly Interface: Easy to navigate interface for efficient use by doctors and other relevant users.
• Secure and Compliant: Ensures patient data privacy and compliance with healthcare regulations.

Name: Team Hackhive

• Adediwura Boluwatife
• Curious Paul
• Bakare

• Backend: Flask
• Frontend: HTML, CSS
• ML/AI: Google Vertex AI
• Other Tools: Google Cloud Storage

Instructions on how to get the project running locally.

• Python 3.x
• pip
• Virtualenv

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# Clone the repository
git clone [repository URL]
cd [repository name]

# Set up a virtual environment (recommended)
python -m venv venv
source venv/bin/activate  # For Windows use `venv\Scripts\activate`

# Install dependencies
pip install -r requirements.txt

# Run the application
export FLASK_APP=app.py 
export FLASK_ENV=development
flask run

• Live Demo -
• Presentation Slide-

Guidelines for team members or other participants who want to contribute.

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1. Fork the project
2. Create your feature branch (`git checkout -b feature/AmazingFeature`)
3. Commit your changes (`git commit -m 'Add some AmazingFeature'`)
4. Push to the branch (`git push origin feature/AmazingFeature`)
5. Open a Pull Request