Event Website
https://sites.google.com/view/3wheart/
Document Type
Event
Start Date
1-12-2022 5:00 PM
Description
Research has shown that the early detection of Heart Disease is critical to treating and understanding the causes. Through the use of advanced machine learning models and com- prehensive data sets collected on patients of varying backgrounds and health statuses, this research shows the listed correlations between attributes of data points and positive identification of the disease. This research uses 1026 unique records and 14 attributes including the classifier of Heart Disease. These attributes range from simple (cholesterol level) to more complex and subjective (chest pain type) but each attribute presents an opportunity to improve each of the analyzed models significantly. Index Terms—WEKA, Machine Learning, Health Data
Included in
GC-258 Heart Disease Prediction using Machine Learning
Research has shown that the early detection of Heart Disease is critical to treating and understanding the causes. Through the use of advanced machine learning models and com- prehensive data sets collected on patients of varying backgrounds and health statuses, this research shows the listed correlations between attributes of data points and positive identification of the disease. This research uses 1026 unique records and 14 attributes including the classifier of Heart Disease. These attributes range from simple (cholesterol level) to more complex and subjective (chest pain type) but each attribute presents an opportunity to improve each of the analyzed models significantly. Index Terms—WEKA, Machine Learning, Health Data
https://digitalcommons.kennesaw.edu/cday/Fall_2022/Graduate_Capstone/4