Comparative Study to Predict the Kidney Disease for the Clinical Data Using Classification Techniques Saluja Gurucharan Singh1, Maheswari N2,* 1Student, School of Computing Science and Engineering, Vellore Institute of Technology, Chennai, India 2Professor, School of Computing Science and Engineering, Vellore Institute of Technology, Chennai, India *Corresponding Author: N Maheswari, E-mail: maheswari.n@vit.ac.in, Professor, School of Computing Science and Engineering, Vellore Institute of Technology, Chennai, India
Online published on 26 September, 2019. Abstract Data mining has proven to be very helpful and extremely effective. It has been used to uncover patterns from big stored information and then used that pattern to build or train classification models. Classification models are helpful to large clinical data for guidance and decision making. Through classification models, the disease can be classified, and also describes that disease is on which stage, from this patient receives better health care services. Kidney is one of the important organs of human body, it extracts waste creatinine and provides purified blood to other organs. Like that, a disease of another organ can also affect the kidney. Kidney disease can be caught by some tests but other diseases can also affect the kidney. This happens when medicinal services authorities utilize data mining projects to recognize and observe patients disease and plan the correct involvement required. So, the causes and effect of disease after period of time, from old data will be predicted using efficient classification techniques. Top Keywords Data Mining, Classification Models, Kidney Disease, Predicted, Medicinal Services. Top |