Predicting transplant outcomes with machine learning.

About This Project

This project applies machine learning to predict outcomes for leukemia patients undergoing transplant procedures. Using clinical data from over 4,600 patients, I developed and evaluated 8 different ML models to provide insights that could help inform treatment decisions.

Key Features

• 8 ML Models – Comprehensive comparison of different algorithms
• Clinical Dataset – Clinical data from 4,600+ patients
• Feature Importance Analysis – Techniques to understand predictions
• Transplant Outcome Prediction – Helping inform treatment decisions

Technical Stack

• Scikit-learn – Machine learning models
• Pandas – Data processing and analysis
• Python – Primary programming language