A Review on Predicting the Stages of Chronic Kidney Disease Using Machine Learning Techniques
Abstract: Kidney Disease refers to the loss of kidney function over the period, whose primary role is to filter the waste from the blood. The count of people suffering from the disease is increasing rapidly and if the person is not diagnosed at the earlier stage it may take the life of the patient. Otherwise, the patient has to undergo transplantation or dialysis. The stages of Chronic Kidney Disease are measured based on Glomerular Filteration Rate (GFR). Various machine learning algorithms are applied for predicting chronic kidney disease. The machine learning techniques namely SVM, Decision Tree, K-NN and Navie Bayes are analyzed.
Keywords: Chronic Kidney Disease, Machine Learning, Classification, Prediction
How to Cite?: Smitha Patil, Dr. Savitha Chowdhary, "A Review on Predicting the Stages of Chronic Kidney Disease Using Machine Learning Techniques", Volume 8 Issue 12, December 2019, International Journal of Science and Research (IJSR), Pages: 837-839, https://www.ijsr.net/getabstract.php?paperid=ART20202042, DOI: https://dx.doi.org/10.21275/ART20202042