A New Approach for Liver Disease Detection using KNN and Back Propagation Algorithm

Authors(2) :-Rahul Sakharam Ishi, Vijay Birchha

Heavy consumption of hybrid food in today's world causes for rising of different diseases. So the study of this medical diagnosis becomes the most important part of disciplines. If there is no proper knowledge of disease then it causes serious effects. Therefore there is a requirement of strong diagnosis system. This is made possible by K-nearest neighbor algorithm and Back propagation neural network. K- Nearest algorithm is based on non-parameterized family used for regression and classification. Back propagation neural network is another technique used for diagnosis of disease based on artificial neural network used for optimization method. In this paper the comparison of both algorithms is presented and how this technique has combinable produced the better result is discussed. The combined approach provides better accuracy up to 96%. Finally frames are provided to identify disease.

Authors and Affiliations

Rahul Sakharam Ishi
SVCE Indore, Madhya Pradesh, India
Vijay Birchha
SVCE Indore, Madhya Pradesh, India

K-NN Algorithm, BPNN, Liver Disease, parameterized.

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Publication Details

Published in : Volume 2 | Issue 6 | November-December 2017
Date of Publication : 2017-12-31
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 549-554
Manuscript Number : CSEIT1726163
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Rahul Sakharam Ishi, Vijay Birchha, "A New Approach for Liver Disease Detection using KNN and Back Propagation Algorithm", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 6, pp.549-554, November-December-2017.
Journal URL : http://ijsrcseit.com/CSEIT1726163

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