Chronic Kidney Disease Prediction System

Abstract

Chronic Kidney Disease prediction is one of the most important issues in medical decision making. The discovery of ckd prediction is an important task because it depends on expertise of doctor’s knowledge. 10% of the population worldwide is affected by chronic kidney disease (CKD), and millions die each year because they do not have access to affordable treatment. The Global Burden of Kidney Disease 2015 study also estimated that, in 2015, 1.2 million people died from kidney failure, an increase of 32% since 2010. Construct effective ckd prediction in time is an essential to prevent healthy patients. Chronic kidney disease is one of the leading cause of death and early prediction of chronic kidney disease is important. Prediction is most interesting and challenging tasks in day to life. Data mining play an essential role for prediction of medical dataset. With innovation and improvement in data-ware housing, data mining, machine learning and emergence of data science as an effective field of utilizing data as a powerful tool to predict useful information, many studies are being conducted to make this process affective . In this study machine learning algorithms (Logistic Regression, Decision Tree, and Random Forest Classifier) will be applied on the health parameters associated with Chronic Kidney Disease to extract hidden patterns on which identification will be done. Chronic Kidney Disease Prediction System would be developed to identify Chronic Kidney Disease before time on the basics of identified attributes and algorithm. Hence precautionary measures would be taken in time. These precautionary measures will help to decrease the death rate caused by Chronic Kidney Disease