Title :
Diagnosis of Thyroid Disorders using Artificial Neural Networks
Author :
Shukla, Anupam ; Tiwari, Ritu ; Kaur, Prabhdeep ; Janghel, R.R.
Author_Institution :
ICT Dept., ABV-IIITM, Gwalior
Abstract :
A major problem in medical science is attaining the correct diagnosis of disease in precedence of its treatment. This paper presents the diagnosis of thyroid disorders using artificial neural networks (ANNs). The feed-forward neural network has been trained using three ANN algorithms; the Back propagation algorithm (BPA), the radial basis function (RBF) Networks and the learning vector quantization (LVQ) networks. The networks are simulated using MATLAB and their performance is assessed in terms of factors like accuracy of diagnosis and training time. The performance comparison helps to find out the best model for diagnosis of thyroid disorders.
Keywords :
backpropagation; diseases; medical diagnostic computing; patient diagnosis; patient treatment; radial basis function networks; vector quantisation; artificial neural network training; back propagation algorithm; disease diagnosis treatment; learning vector quantization; radial basis function network; thyroid disorder; Artificial neural networks; Back; Diseases; Feedforward neural networks; Feedforward systems; MATLAB; Medical diagnostic imaging; Medical treatment; Neural networks; Vector quantization; Artificial Neural Networks; Backpropagation Networks; Diagnosis; Learning Vector Quantization Networks; Radial Basis Function Networks; Thyroid disorders;
Conference_Titel :
Advance Computing Conference, 2009. IACC 2009. IEEE International
Conference_Location :
Patiala
Print_ISBN :
978-1-4244-2927-1
Electronic_ISBN :
978-1-4244-2928-8
DOI :
10.1109/IADCC.2009.4809154
