Development of a Cardiovascular Disease Risk Prediction System using Machine Learning and Patient Health Data
Welcome to the CVD System Repository! This repository contains my thesis on developing a comprehensive Cardiovascular Disease (CVD) system, along with the resources necessary to understand and reproduce the work.
Within this repository, you will find:
-
MSC Dissertation Document: The dissertation provides detailed insights into the development of the CVD system, including the methodology, experiments, and results.
-
Jupyter Notebook: The Jupyter Notebook showcases the step-by-step process of exploring the Framingham dataset, applying data cleansing techniques, and building the predictive model for the CVD system.
-
Original Dataset: The original Framingham dataset is included in this repository, allowing you to access the raw data used for developing the CVD system.
-
Documentation: The documentation that accompanies the Framingham dataset, provided by the National Heart, Lung, and Blood Institute, is also available. It offers important information about the dataset's variables, data collection procedures, and study design.
I would like to extend my gratitude to the National Heart, Lung, and Blood Institute for providing the Framingham dataset, which has been instrumental in the development of this CVD system.
Feel free to explore the contents of this repository, delve into the dissertation and Jupyter Notebook, and leverage the resources to gain a deeper understanding of the CVD system's creation and implementation.
Jason Jay Dookarun University of Surrey MSc Data Science Student 31 August 2023