An ml model that predict the likelihood of a person having tuberculosis

This project is a Tuberculosis (TB) prediction system that uses machine learning to identify potential TB cases. The system is designed to assist healthcare providers in early diagnosis by analyzing patient data.

• Machine learning-based prediction for TB diagnosis.
• Focus on early detection to improve treatment outcomes.
• Scalable and adaptable to different datasets.

• Python: Core programming language.
• scikit-learn: Machine learning framework.
• Pandas, NumPy: Data preprocessing and analysis.
• Matplotlib, Seaborn: Data visualization.

1. Clone the repository:

   git clone [repository-url]
   cd tb_pred

2. Install the required dependencies:

   pip install -r requirements.txt

3. Run the script to train the model and make predictions:

   python tbpred.py

• Incorporate more advanced machine learning models (e.g., deep learning).
• Develop a web interface for easier use.
• Validate the model with real-world datasets.

Feel free to reach out if you have questions or suggestions about these projects!