학술논문
Machine Learning-Based Prediction of Coronary Heart Disease
Document Type
Conference
Source
2023 9th International Conference on Control, Instrumentation and Automation (ICCIA) Control, Instrumentation and Automation (ICCIA), 2023 9th International Conference on. :1-5 Dec, 2023
Subject
Language
Abstract
Coronary Heart Disease (CHD) remains a significant global health concern. This study utilizes the Sleep Heart Health Study (SHHS) dataset, encompassing demographic features, measurement features, and combination of these two categories, to develop a predictive model for CHD risk. The Multi-Layer Perceptron (MLP) neural network is employed to capture intricate relationships within the data. An accuracy mostly greater than 70% in CHD risk prediction is exhibited by the MLP model when categories of selected features are fed to it. This research emphasizes the importance of using readily available data for physicians and advanced machine learning technique to enhance early CHD risk prediction. These findings have the potential to improve personalized medicine and targeted interventions for CHD prevention and management.