Automatic hepatitis diagnosis system based on Linear Discriminant Analysis and Adaptive Network based on Fuzzy Inference System

Authors:
Esin Dogantekin;Akif Dogantekin;Derya Avci
Affiliations:
Firat University, Firat Medicine Center, Department of Microbiology and Clinical Microbiology, 23119 Elazig, Turkey;Firat University, Firat Medicine Center, Department of Internal Diseases, 23119 Elazig, Turkey;Bahcelievler Primary School, Elazig, Turkey
Venue:
Expert Systems with Applications: An International Journal
Year:
2009

Citing 9
Cited 7

Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection

IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast Linear Discriminant Analysis Using Binary Bases

ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 02
A decision support system based on support vector machines for diagnosis of the heart valve diseases

Computers in Biology and Medicine
An expert system based on Wavelet Neural Network-Adaptive Norm Entropy for scale invariant texture classification

Expert Systems with Applications: An International Journal
Hepatitis disease diagnosis using a new hybrid system based on feature selection (FS) and artificial immune recognition system with fuzzy resource allocation

Digital Signal Processing
Principles component analysis, fuzzy weighting pre-processing and artificial immune recognition system based diagnostic system for diagnosis of lung cancer

Expert Systems with Applications: An International Journal
An expert system approach based on principal component analysis and adaptive neuro-fuzzy inference system to diagnosis of diabetes disease

Digital Signal Processing
Comparison of wavelet families for texture classification by using wavelet packet entropy adaptive network based fuzzy inference system

Applied Soft Computing
Intelligent target recognition based on wavelet adaptive network based fuzzy inference system

IbPRIA'05 Proceedings of the Second Iberian conference on Pattern Recognition and Image Analysis - Volume Part I

A new hybrid method based on local fisher discriminant analysis and support vector machines for hepatitis disease diagnosis

Expert Systems with Applications: An International Journal
A Study on Hepatitis Disease Diagnosis Using Multilayer Neural Network with Levenberg Marquardt Training Algorithm

Journal of Medical Systems
A vision-based regression model to evaluate Parkinsonian gait from monocular image sequences

Expert Systems with Applications: An International Journal
Automatic disease diagnosis systems using pattern recognition based genetic algorithm and neural networks

AIASABEBI'11 Proceedings of the 11th WSEAS international conference on Applied informatics and communications, and Proceedings of the 4th WSEAS International conference on Biomedical electronics and biomedical informatics, and Proceedings of the international conference on Computational engineering in systems applications
A Study on Hepatitis Disease Diagnosis Using Probabilistic Neural Network

Journal of Medical Systems
Hepatitis disease diagnosis using a novel hybrid method based on support vector machine and simulated annealing (SVM-SA)

Computer Methods and Programs in Biomedicine
A Novel Radial Basis Function Networks Locally Tuned with Differential Evolution for Classification: An Application in Medical Science

International Journal of Systems Biology and Biomedical Technologies

Quantified Score

Hi-index	12.05

Visualization

Abstract

In this paper, an automatic diagnosis system based on Linear Discriminant Analysis (LDA) and Adaptive Network based on Fuzzy Inference System (ANFIS) for hepatitis diseases is introduced. This automatic diagnosis system deals with the combination of feature extraction and classification. This automatic hepatitis diagnosis system has two stages, which feature extraction - reduction and classification stages. In the feature extraction - reduction stage, the hepatitis features were obtained from UCI Repository of Machine Learning Databases. Then, the number of these features was reduced to 8 from 19 by using Linear Discriminant Analysis (LDA). In the classification stage, these reduced features are given to inputs ANFIS classifier. The correct diagnosis performance of the LDA-ANFIS automatic diagnosis system for hepatitis disease is estimated by using classification accuracy, sensitivity and specificity analysis, respectively. The classification accuracy of this LDA-ANFIS automatic diagnosis system for the diagnosis of hepatitis disease was obtained in about 94.16%.