Chronic Kidney Disease for Collaborative Healthcare Data Analytics using Random Forest Classification Algorithms

Collaborative Healthcare data analytics is a method of methodical data analysis that allows healthcare specialists to discovery opportunities used for development in health system management processing the various information are stored. This proposed approach entails three parts comparable to preprocessing, attribute selection, classification algorithms. The goal of this work is to plan a machine-based diagnostic approach using machine learning technique. This method is developed to mining the risk factors of chronic kidney diseases. There are many improved algorithms consume stayed proposed in every recent years. These algorithms improve the effectiveness of mining risk of Chronic Kidney Disease, but there are also shortcomings. In this work, Random forest, SVM and ANN algorithms were used to identify an early diagnosis of CKD patients with good accuracy.