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

Format: Volume 5, Issue 1, No 5, 2017

Copyright: All Rights Reserved ©2017

Year of Publication: 2017

Author: P.LauraJuliet,Dr.P.R.Tamilselvi

Reference:IJCS-177

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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

[1] A.S. Aneeshkumar and C. JothiVenkateswaran, Estimating the Survallience of Liver Disorder using Classification Algorithms, International Journal of Computer Applcations, Vol 57- No.6, pp. 39-42, November 2012. [2] AnjuGulia ,Dr.RajanVohra , Praveen Rani, Liver Patient Classification Using Intelligent Techniques, International Journal of Computer Science and Information Technologies, Vol. 5 (4) , pp. 5110-5115, 2014. [3] BendiVenkataRamana, Prof. M. Surendra Prasad Babu, Prof. N. B. Venkateswarlu, A Critical Comparative Study of Liver Patients from USA and INDIA: An Exploratory Analysis, International Journal of Engineering Research and Development, Volume 1, Issue 6, PP.17-24, June 2012. [4] BendiVenkataRamana, Prof. M.Surendra Prasad Babu , “Liver Classification Using Modified Rotation Forest”, International Journal of Engineering Research and Development, Volume 1, PP.17-24, Issue 6, June 2012. [5] Ch. Sanjeev Kumar Dash and PulakSahoo, An Empirical Analysis of Evolved Radial Basis Function Networks and Support Vector Machines with Mixture of Kernels. International Journal onArtificial Intelligence Tools, Vol. 24, No. 4 ,2015.


Keywords

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

This work is licensed under a Creative Commons Attribution 3.0 Unported License.   

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