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- W4384135368 abstract "The heart is the crucial organ of the human body that aids in the coursing and filtering of blood to every one of the parts of the body and the heart itself. In the world, millions of deaths are due to cardiovascular diseases each year. Some of cardiovascular diseases include Heart failure, cardiomyopathy, cardiac dysrhythmia, hypertension, Stroke, and pulmonary heart disease. Some common indications or symptoms are dyspnea, palpitation, dizziness, fatigue, angina, sweating, and nausea. This review includes a brief in-depth analysis of machine learning (ML) techniques for the prediction of heart diseases that are available in the literature. The machine learning techniques that are discussed are Random Forest, Support Vector Machine (SVM), Artificial neural network (ANN), Naïve Bayes (NB), Decision Tree (DT) and K-nearest neighbor (KNN). Furthermore, all these mentioned techniques are compared on basis of their features." @default.
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- W4384135368 date "2023-01-01" @default.
- W4384135368 modified "2023-09-24" @default.
- W4384135368 title "Machine Learning Techniques in Cardiovascular Disease Prediction" @default.
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- W4384135368 doi "https://doi.org/10.1007/978-3-031-35641-4_16" @default.
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