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Not Detecting Disease at early stage is one of the biggest threats and results in loss of lives. The detection of disease at the right stage paves way for proper diagnosis and medications, for pathologist and doctors to support their decisions. Machine learning being implemented in all domains for better results, applying ML in medical field plays a major role in diagnosing diseases and recommendation of medication for the diagnosed disease. . The main objective is to present an effective approach for the chronic kidney disease(CKD) diagnosis using artificial neural network (ANN), by filling the missing values of the dataset using mean, mode and median of attributes. Further, trained Neural Network classifier to evaluate the detection performances on separate test dataset. A simple web based, prediction of CKD using user input is developed.
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