Portfolio

Chronic kidney disease (CKD) affects millions globally, progressively reducing kidney function and requiring careful monitoring to manage effectively. My project addresses this challenge by creating a comprehensive data analytics application that tracks disease progression, predicts outcomes, and provides personalized interventions. Using the UCI Machine Learning Repository’s CKD dataset, I’ve developed an interactive dashboard that enables healthcare providers to visualize patient data, calculate risk scores, and generate tailored recommendations. The system combines data engineering, predictive modeling, and clinical decision support in a user-friendly Streamlit interface. This portfolio project demonstrates my ability to apply data science to real-world healthcare problems, with a detailed Medium article that explores the technical implementation and potential impact on patient care, including some personal reasons as to why I followed through with this project!

Github