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- W2186123423 abstract "The diagnosis of diseases is a crucial and difficult job in medicine. The recognition of heart disease from diverse features or signs is a multi-layered problem that is not free from false assumptions and is frequently accompanied by hasty effects (1). Thus an attempt to exploit knowledge and experience of several specialists and clinical screening data of patients composed in databases to assist the diagnosis procedure is regarded as a great challenge. The healthcare industry gathers enormous amounts of heart disease data that unfortunately, are not mined to determine concealed information for effective diagnosing (2). In this paper, an efficient approach for the intelligent heart disease prediction based on Probabilistic Neural Network (PNN) technique is proposed. Initially, the data set containing 13 medical attributes were obtained from the Cleveland heart disease database. The dataset is clustered with the aid of k-means clustering algorithm. The PNN with radial basis function is trained using the selected data sets. The comparison between existing approaches and proposed approach with respect to accuracy of prediction, sensitivity and specificity is recorded in this paper. The results from experiments returned with diminishing fact that there is considerable improvement in classification and prediction. The proposed PNN works as promising tool for prediction of heart disease." @default.
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- W2186123423 date "2013-01-01" @default.
- W2186123423 modified "2023-09-30" @default.
- W2186123423 title "Intelligent Heart Disease Prediction System Using Probabilistic Neural Network" @default.
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