Kidney Clinical Trial Eligibility Predictor

This project utilizes a Random Forest Classifier to predict whether a person qualifies for clinical trials based on specific health parameters. The model is integrated into a Streamlit web app for easy input and real-time predictions.

Features

• Machine learning-based classification system for clinical trial eligibility.
• User-friendly interface built with Streamlit.
• Trained using Scikit-learn with patient health data.
• Achieves 98.75% accuracy in eligibility prediction.
• Model storage and retrieval optimized using joblib.

Installation

pip install -r requirements.txt

Usage

streamlit run app.py

Technologies Used

• Python
• Streamlit
• Scikit-learn
• joblib
• pandas

License

This project is licensed under the MIT License.