Improvement of the Performance of Models for Predicting Coronary Artery Disease Based on XGBoost Algorithm and Feature Processing Technology

Improvement of the Performance of Models for Predicting Coronary Artery Disease Based on XGBoost Algorithm and Feature Processing Technology

Coronary artery disease (CAD) is one of the diseases with the highest morbidity and mortality in the world. In 2019, the number of deaths caused by CAD reached 9.14 million. The detection and treatment of CAD in the early stage is crucial to save lives and improve prognosis. Therefore, the purpose o...

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Bibliographic Details
Main Authors:	Shasha Zhang, Yuyu Yuan, Zhonghua Yao, Xinyan Wang, Zhen Lei
Format:	Article
Language:	English
Published:	MDPI AG 2022-01-01
Series:	Electronics
Subjects:	cardiovascular disease coronary artery disease feature smoothing feature encoding feature selection feature construction
Online Access:	https://www.mdpi.com/2079-9292/11/3/315

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