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Comparative Study on Heart Disease Prediction Using Feature Selection Techniques on Classification Algorithms
2021
Applied Computational Intelligence and Soft Computing
Heart disease is recognized as one of the leading factors of death rate worldwide. Biomedical instruments and various systems in hospitals have massive quantities of clinical data. Therefore, understanding the data related to heart disease is very important to improve prediction accuracy. This article has conducted an experimental evaluation of the performance of models created using classification algorithms and relevant features selected using various feature selection approaches. For results
doi:10.1155/2021/5581806
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