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- W2995512232 abstract "Taking care of the health of people is one of the challenging tasks in the world. Cardiovascular disease is one of the main factors that increase mortality. In order to detect this heart defect, it would be necessary to look for a system able to predict its existence and prevent heart diseases that continues to drastically increase. In this paper, we improved the quality of cardiovascular disease prediction using a better preprocessing phase. It helps in identifying a heart disease of a patient and guide a doctor to better diagnose whether a person has cardiovascular disease or not. To prove our results, we have done a comparison between different Machine Learning algorithms using accuracy, precision, f1-score and recall performance metrics." @default.
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- W2995512232 date "2019-10-01" @default.
- W2995512232 modified "2023-10-16" @default.
- W2995512232 title "Identification of Cardiovascular Diseases Using Machine Learning" @default.
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- W2995512232 doi "https://doi.org/10.1109/cmt.2019.8931411" @default.
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