ZHONGLIANG SHI (17221268) - Team Leader
SUNNY CHAN ZI YANG (S2022037)
HO RU XIN (S2023921)
FANYUE (17220701)
According to the World Health Organization (WHO), heart disease is the leading cause of death globally for the last 20 years. However, it is now killing more people than ever before. The number of deaths from heart disease increased by more than 2 million since 2000, to nearly 9 million in 2019. Heart disease now represents 16% of total deaths from all causes.
Due to this reason, heart disease prediction remains as one of the most important research area in the health care sector to improve prevention and reduce mortality. Making use of the advancing computing technology, early prediction of heart disease is now possible with the help of machine learning.
To develop a web application that can provide healthcare assistance to patients and healthcare providers by visualizing the variables in a heart disease dataset and predicting the risk of heart disease using machine learning.
Users and healthcare providers will be able to explore the variables of heart disease and predict the risk of heart disease, thereby enabling users to make healthier lifestyle choices and assisting healthcare providers in making better clinical decisions.
1. What are the differences in heart disease conditions among different countries? 2. What insights could we draw from the heart disease data? 3. How to predict heart disease? 4.How to interactively visualize the results of analysis and deploy the prediction model?
1. Business Understanding (Problem Identification, set objective) 2. Data Understanding (Data collection, data description, Exploratory Data Analysis) 3. Data Preparation (data selection, data cleaning, data transformation) 4. Modeling (SVM method for predictive modeling) 5. Evaluation (Evaluate the predictive model using confusion matrix) 6. Deployment of Shiny application for visualization of results
1. Identification of an existing problem based on real-life experience. 2. Interactive visualization of analysis results. 3. First-hand experience of developing a web-based application using Shiny.
1. World Health Organization (WHO) 2. Centers for Disease Control and Prevention (CDC) 3. UCI Heart Disease Dataset (Cleveland) 4. Our World in Data: Share of Deaths from Heart Disease, 1990 to 2017
Heart Disease Analysis Shiny Application
R Documentation in GitHub
Video Presentation