IEEE.Peter, T. John, and K. Somasundaram. "An empirical study on prediction of heart disease using classification data mining techniques." Advances in Engineering, Science and Management (ICAESM), 2012 International Conference on. IEEE, 2012....
Heart disease is a fatal human disease, rapidly increases globally in both developed and undeveloped countries and consequently, causes death. Normally, in this disease, the heart fails to supply a sufficient amount of blood to other parts of the body in
Heart disease, also called cardiovascular disease, is considered one of the deadliest diseases that cause high mortality worldwide. Early detection or prediction is a challenging task in the medical field. There is a massive amount of data in the healthcare industry, and processing this amount of...
This research provides an overview of feature selection and classification methods for the prediction of heart disease in the last ten years. Thus, it can be used as a reference in choosing a method for heart disease prediction for ... FF Firdaus,HA Nugroho,I Soesanti - Universitas Gadjah Ma...
Heart Disease (CHD) is a high-mortality disease, and there are non-public and significant differences in CHD datasets for current research, which makes it difficult to perform unified transfer learning. Therefore, in this paper, we propose a novel adversarial domain-adaptive multichannel graph ...
Intelligent Bi-LSTM with Architecture Optimization for Heart Disease Prediction in WBAN through Optimal Channel Selection and Feature Selection Wireless Body Area Network (WBAN) is a trending technology of Wireless Sensor Networks (WSN) to enhance the healthcare system. This system is developed to .....
Heart disease is one the leading causes of death globally, making the early detection of it crucial. Emerging technologies such as machine learning and deep learning are now being actively used in biomedical care, healthcare, and disease prediction. The focus of this paper is on the prediction ...
Sanjib Ghosh and Muhammad Alamgir Islam. Performance Evaluation and Comparison of Heart Disease Prediction Using Machine Learning Methods with Elastic Net Feature Selection.American Journal of Applied Mathematics and Statistics. 2023; 11(2):35-49. doi: 10.12691/ajams-11-2-1 ...
The present study examines the role of feature selection methods in optimizing machine learning algorithms for predicting heart disease. The Cleveland Heart disease dataset with sixteen feature selection techniques in three categories of filter, wrapper,
A medical check-up during driving enables the early detection of diseases. Heartbeat irregularities indicate possible cardiovascular diseases, which can be determined with continuous health monitoring. Therefore, we develop a redundant sensor system base