The week's pick
Reseach Article
Improved MLP-NN based approach for Lung Diseases Classification
by
Ramandeep Kaur,
Prince Verma
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 131 - Number 6 |
| Year of Publication: 2015 |
| Authors: Ramandeep Kaur, Prince Verma |
10.5120/ijca2015907472
|
Ramandeep Kaur, Prince Verma . Improved MLP-NN based approach for Lung Diseases Classification. International Journal of Computer Applications. 131, 6 ( December 2015), 22-26. DOI=10.5120/ijca2015907472
@article{
10.5120/ijca2015907472,
author = {
Ramandeep Kaur,
Prince Verma
},
title = { Improved MLP-NN based approach for Lung Diseases Classification },
journal = {
International Journal of Computer Applications
},
issue_date = { December 2015 },
volume = { 131 },
number = { 6 },
month = { December },
year = { 2015 },
issn = { 0975-8887 },
pages = {
22-26
},
numpages = {9},
url = {
https://ijcaonline.org/archives/volume131/number6/23454-2015907472/
},
doi = { 10.5120/ijca2015907472 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:26:34.278100+05:30
%A Ramandeep Kaur
%A Prince Verma
%T Improved MLP-NN based approach for Lung Diseases Classification
%J International Journal of Computer Applications
%@ 0975-8887
%V 131
%N 6
%P 22-26
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract
The Data Mining is extracting or mining knowledge from large volume of data. Classification technique is used in different-2 application. In this paper proposes a new classifier utilizing MLP approach by grouping based on nearest neighbor i.e. improved MLP-NN. The MLP-NN approach can handle noisy data and reduce complexity. This technique has been applied for medical diagnosis. This paper analyzes the lung images (i.e. CT-scan images) for identifying and classifying them among the various lung diseases (i.e. bronchitis, emphysema, pleural effusion or normal) using 100 images data set and 80 images data set.
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Index Terms
Computer Science
Information Sciences
Keywords