Proceeding of

NCAICN National Conference 2013



Advances in

Computing & Networking


A Special Issue of

International Journal of Computer Science and Applications



Hon. Shri Sundeepji Meghe

(Chairman, Vidarbha Youth Welfare Society, Amravati)



Dr. V.T. Ingole (FIE, FIETE, Professor Emeritus)


Organizing Committee


Dr. D.T. Ingole (FIE, FIETE)

(Principal PRMIT & R, Badnera and  Chairman IEI  Amravati Center).


 Er. A.W. Jawanjal

(Honorary Secretary IEI, Amravati Center)


Dr. G.R. Bamnote ((FIE, FIETE)

(H.O.D. Computer Science & Engineering)

Dr. A.S. Alvi (MIE)

(H.O.D. Information Technology))

Prof. Mrs. M.D. Ingole (FIE.MIETE)

(H.O.D. Electronics & Telecommunication)


Prof. S.V. Dhopte ((FIE, FIETE)

Prof. Ms. V.M. Deshmukh (FIE, FIETE)

Dr. S.W. Mohod  (FIE,FIETE)


Dr. S.R. Gupta (MIE, MIETE)

Prof. S.V. Pattalwar ((FIE, FIETE)

Prof. M.D. Damahe


Prof. Mrs. M.S. Joshi                

Dr. S.M. Deshmukh

Prof. V.U. Kale

Prof. S.S. Kulkarni

Prof. Ms. R.R. Tuteja

Prof. Ms. J.N. Ingole

Prof. V.R. Raut

Prof. C.N. Deshmukh

Prof. Ms. M.S. Deshmukh

Prof. S.P. Akarte

Prof. Mrs. A.P. Deshmukh

Prof. Mrs. S.S. Sikchi

Prof. N.N. Khalsa

Department of Information and Computer Science and Engineering

Prof. Ram Meghe Institute of Technology and Research, Badnera Distt. Amravati



Prof. K. H. Walse





IJCSA ISSN: 0974-1011 (Online) >>    

Comparison of performance of ANN to classify the type of Erythemato-Squamous Disease

Dr. Mrs. S. N. Kale and Dr. S.V. Dudul


Neural network architectures are configured to perform optimally based on the various dataset. In this paper, various NN architectures are built with different parameters. Here the dataset used is the benchmark dataset of erythemato-squamous diseases. The differential diagnosis of erythemato-squamous diseases is a difficult problem in dermatology. Artificial Neural Network (ANN) classifies the given samples when trained and nearly 98% classification accuracy is achieved. Generalized Feed Forward Neural Network (FFNN) can solve the multivariable classification problem of determination of skin disease. The performance of MLPNN, RBFNN, Modular NN, SOFM and Recurrent ANN are also studied to determine the type of Erythemato-Squamous Disease, which all share the clinical features of erythema and scaling, with very little differences. The diseases are classified into six classes, namely psoriasis, seboreic dermatitis, lichen planus, pityriasis rosea, chronic dermatitis, and pityriasis rubra pilaris.

2013 International Journal of Computer Science and Applications 

Published by Research Publications, India