@article{ART002843528},
author={Young-Dan Noh and Kyu-Cheol Cho},
title={Heart Disease Prediction Using Decision Tree With Kaggle Dataset},
journal={Journal of The Korea Society of Computer and Information},
issn={1598-849X},
year={2022},
volume={27},
number={5},
pages={21-28},
doi={10.9708/jksci.2022.27.05.021}
TY - JOUR
AU - Young-Dan Noh
AU - Kyu-Cheol Cho
TI - Heart Disease Prediction Using Decision Tree With Kaggle Dataset
JO - Journal of The Korea Society of Computer and Information
PY - 2022
VL - 27
IS - 5
PB - The Korean Society Of Computer And Information
SP - 21
EP - 28
SN - 1598-849X
AB - All health problems that occur in the circulatory system are refer to cardiovascular illness, such as heart and vascular diseases. Deaths from cardiovascular disorders are recorded one third of in total deaths in 2019 worldwide, and the number of deaths continues to rise. Therefore, if it is possible to predict diseases that has high mortality rate with patient’s data and AI system, they would enable them to be detected and be treated in advance. In this study, models are produced to predict heart disease, which is one of the cardiovascular diseases, and compare the performance of models with Accuracy, Precision, and Recall, with description of the way of improving the performance of the Decision Tree(Decision Tree, KNN (K-Nearest Neighbor), SVM (Support Vector Machine), and DNN (Deep Neural Network) are used in this study.).
Experiments were conducted using scikit-learn, Keras, and TensorFlow libraries using Python as Jupyter Notebook in macOS Big Sur. As a result of comparing the performance of the models, the Decision Tree demonstrates the highest performance, thus, it is recommended to use the Decision Tree in this study.
KW - heart disease;diseases that has high morality rate;AI;detected;Decision Tree
DO - 10.9708/jksci.2022.27.05.021
ER -
Young-Dan Noh and Kyu-Cheol Cho. (2022). Heart Disease Prediction Using Decision Tree With Kaggle Dataset. Journal of The Korea Society of Computer and Information, 27(5), 21-28.
Young-Dan Noh and Kyu-Cheol Cho. 2022, "Heart Disease Prediction Using Decision Tree With Kaggle Dataset", Journal of The Korea Society of Computer and Information, vol.27, no.5 pp.21-28. Available from: doi:10.9708/jksci.2022.27.05.021
Young-Dan Noh, Kyu-Cheol Cho "Heart Disease Prediction Using Decision Tree With Kaggle Dataset" Journal of The Korea Society of Computer and Information 27.5 pp.21-28 (2022) : 21.
Young-Dan Noh, Kyu-Cheol Cho. Heart Disease Prediction Using Decision Tree With Kaggle Dataset. 2022; 27(5), 21-28. Available from: doi:10.9708/jksci.2022.27.05.021
Young-Dan Noh and Kyu-Cheol Cho. "Heart Disease Prediction Using Decision Tree With Kaggle Dataset" Journal of The Korea Society of Computer and Information 27, no.5 (2022) : 21-28.doi: 10.9708/jksci.2022.27.05.021
Young-Dan Noh; Kyu-Cheol Cho. Heart Disease Prediction Using Decision Tree With Kaggle Dataset. Journal of The Korea Society of Computer and Information, 27(5), 21-28. doi: 10.9708/jksci.2022.27.05.021
Young-Dan Noh; Kyu-Cheol Cho. Heart Disease Prediction Using Decision Tree With Kaggle Dataset. Journal of The Korea Society of Computer and Information. 2022; 27(5) 21-28. doi: 10.9708/jksci.2022.27.05.021
Young-Dan Noh, Kyu-Cheol Cho. Heart Disease Prediction Using Decision Tree With Kaggle Dataset. 2022; 27(5), 21-28. Available from: doi:10.9708/jksci.2022.27.05.021
Young-Dan Noh and Kyu-Cheol Cho. "Heart Disease Prediction Using Decision Tree With Kaggle Dataset" Journal of The Korea Society of Computer and Information 27, no.5 (2022) : 21-28.doi: 10.9708/jksci.2022.27.05.021