Cardiovascular-Disease-Dataset

This repository contains project materials for the Winter STAT 232 class, University of California, Riverside, A. Gary Anderson School of Management.

Introduction

For those who are new to this folder, the Project-Code.Rmd, Project-Code.html, and Project-Code.Rproj files are our main coding files. This project is completed using R Markdown in R Studio. The data is originally obtained from Kaggle.com, link will be attached below. Feel free to explore more options beyond this analysis report.

Project Idea

This project focuses on analyzing a cardiovascular disease dataset to develop predictive models that can identify individuals at risk of developing cardiovascular diseases. Using various data analysis and machine learning techniques, we aim to uncover significant patterns and risk factors associated with cardiovascular conditions. The project involves data preprocessing, exploratory data analysis, feature selection, and model training and evaluation. The ultimate goal is to create a reliable prediction model that can aid healthcare providers in early detection and prevention of cardiovascular diseases, ultimately contributing to better patient outcomes and public health strategies.

Contents

• Project-Code.Rmd: This contains the R Markdown code which contains most of our analysis coding.
• Project-Code.html: HTML export of the R Markdown file for easy reading.
• Final-Report.docs: Documents which reports our finding and analysis during the project.
• Data Folder: Contains the datasets used for analysis. This dataset is uploaded by Svetlana Ulianova. Disclaimer: The data is obtained from Kaggle.com Cardiovascular Disease Dataset. All data are used for educational purposes only. Do not republish Ulianova's work without approval. License: Data files are copyrighted by the original authors

License

This project is licensed under the MIT License. See the LICENSE file for more details.

Contributing

This project had been finished at March 2024, no changes shall be made to this main repository. No edits will be approved.

Contact

If you have any questions or need further information, please contact our team at: [email protected]

Authors:

• Nathaniel Zhu
• Ankit Malhotra
• Hong Che