Online ISSN: 2515-8260


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Dr.M.Rajaiah1 ,Ms.EswararajuHemasri2 ,Ms. Damai Venkamma3 ,Mr. Annapureddy Teja4 ,Mr. Bulagakula Gowtham5


ABSTRACT_ Huge volumes of healthcare data are gathered by the industry, but regrettably they are not "mined" to reveal hidden information for efficient analysis, diagnosis, and decision-making. Finding hidden patterns and linkages frequently involves idle. Advanced data mining methods can assist and offer a solution to deal with this scenario. The technique of extracting hidden information from a large dataset is known as data mining. Clustering, classification, association analysis, regression, and other data mining techniques summarization, analysis of time series and sequences, etc. Data mining methods are important a crucial part in several fields including text mining, graph mining, medical mining, Web mining and mining of multimedia. The goal of this research project is to forecast renal Utilizing Artificial Neural Networks (ANN) and Support Vector Machine (SVM). This study compares the accuracy and execution times of these two algorithms in order to assess how well they function. According to the experimental findings, the ANN performs better than the alternative approach.

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