Shahid Mohammad Ganie1, Pijush Kanti Dutta Pramanik2, Majid Bashir Malik3, Anand Nayyar4, Kyung Sup Kwak5,*
Computer Systems Science and Engineering, Vol.46, No.3, pp. 3993-4006, 2023, DOI:10.32604/csse.2023.035244
Abstract Cardiovascular disease is among the top five fatal diseases that affect
lives worldwide. Therefore, its early prediction and detection are crucial, allowing
one to take proper and necessary measures at earlier stages. Machine learning
(ML) techniques are used to assist healthcare providers in better diagnosing heart
disease. This study employed three boosting algorithms, namely, gradient boost,
XGBoost, and AdaBoost, to predict heart disease. The dataset contained heart disease-related clinical features and was sourced from the publicly available UCI ML
repository. Exploratory data analysis is performed to find the characteristics of
data samples about descriptive and inferential statistics. Specifically, it was… More >