A SURVEY ON CLASSIFICATION TECHNIQUES IN DATA MINING FOR EARLY DETECTION OF LIVER DISEASE FROMINDIAN LIVER PATIENTS DATA

Sri Vasavi College, Erode Self-Finance Wing, 3rd February 2017. National Conference on Computer and Communication, NCCC’17. International Journal of Computer Science (IJCS) Published by SK Research Group of Companies (SKRGC)

Abstract

Data mining techniques plays a very important role in health care industry to predict and diagnosis the disease in early stage with the use of machine learning tool. Liver disease is one of the growing diseases these days due to the changed life style of people. Various authors have worked in the field of classification of data and they have used various classification techniques like Decision Tree, Support Vector Machine, Naïve Bayes, Artificial Neural Network etc. These techniques are useful in timely and accurate classification and prediction of diseases and better care of patients. The main focus of this work is to analyse the use of data mining techniques by different authors for the prediction and classification ofliver disease. The dataset used in this work is Liver functional test data from Indian liver patients.

References

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Keywords

Data Mining, Classification Techniques, liver disease, Liver Functional Test Data ,Indian Liver Patients.