Healthify is a machine learning-based project developed in Python that predicts diseases based on patient symptoms. It incorporates Decision Tree, Random Forest, and Naive Bayes algorithms to enhance accuracy, achieving up to 80% precision.

1. Clone this repository to your local machine:

   git clone https://github.com/Sam23599/Healthify

2. Install the required dependencies:

   pip install numpy pandas pillow opencv-python scikit-learn

1. Run the main file clean_code.py to launch the GUI.
2. Enter symptoms for prediction.
3. Click on the respective buttons for prediction based on Decision Tree, Random Forest, or Naive Bayes.
4. View the predicted disease in the GUI.

• Training Data: Training.csv
• Testing Data: Testing.csv

• Utilizes tkinter for GUI.
• Implements Decision Tree, Random Forest, and Naive Bayes algorithms.
• Achieves 80% precision accuracy in disease prediction.

• Satyam Singh Virat ([email protected])

This project is licensed under the MIT License - see the LICENSE file for details.

Feel free to modify this README to suit your project's details and structure. If you have any questions or need further assistance, don't hesitate to reach out.