Diagnosing Hepatitis Disease by Using Fuzzy

Aims: Nowadays, computational intelligence is frequently used in diagnosis and determination of the severity of various diseases. In fact, different tools of computational intelligence help physicians as an assistant t

[1]  M. P. Windham.  Geometrical fuzzy clustering algorithms , 1983 .

[2]  S. Mori,et al.  Fuzzy scheduling of the parameters in Hopfield neural networks , 1993, Proceedings of 1993 International Conference on Neural Networks (IJCNN-93-Nagoya, Japan).

[3]  Pau-Choo Chung,et al.  Endocardial boundary detection using a neural network , 1993, Pattern Recognit..

[4]  Atam P. Dhawan,et al.  Edge detection using a Hopfield neural network , 1994 .

[5]  James E. Steck,et al.  Use of Hopfield neural networks in optimal guidance , 1994 .

[6]  K. Cheng,et al.  Multispectral magnetic resonance images segmentation using fuzzy Hopfield neural network. , 1996, International journal of bio-medical computing.

[7]  Sadaaki Miyamoto,et al.  An overview and new methods in fuzzy clustering , 1998, 1998 Second International Conference. Knowledge-Based Intelligent Electronic Systems. Proceedings KES'98 (Cat. No.98EX111).

[8]  W. Dich,et al.  Minimal distance neural methods , 1998, 1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36227).

[9]  June Ho Park,et al.  Adaptive Hopfield neural networks for economic load dispatch , 1998 .

[10]  Tzu-ch'ing Wang,et al.  Fuzzy neural network for edge detection and Hopfield network for edge enhancement , 1999 .

[11]  Wlodzislaw Duch,et al.  Optimization of logical rules derived by neural procedures , 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

[12]  Chuan-Yu Chang,et al.  Two-layer competitive based Hopfield neural network for medical image edge detection , 2000 .

[13]  Rüdiger W. Brause,et al.  Medical Analysis and Diagnosis by Neural Networks , 2001, ISMDA.

[14]  Jzau-Sheng Lin.  Fuzzy-possibilistic neural network to vector quantizer in frequency domains , 2002 .

[15]  Yu-Tai Ching,et al.  Fuzzy Hopfield neural network with fixed weight for medical image segmentation , 2002 .

[16]  Tulay Yildirim,et al.  Artificial neural networks for diagnosis of hepatitis disease , 2003, Proceedings of the International Joint Conference on Neural Networks, 2003..

[17]  Robert Ivor John,et al.  Computer aided fuzzy medical diagnosis , 2004, Inf. Sci..

[18]  James Lam,et al.  Stochastic stability analysis of fuzzy hopfield neural networks with time-varying delays , 2005, IEEE Transactions on Circuits and Systems II: Express Briefs.

[19]  Kemal Polat,et al.  A Novel Approach to Resource Allocation Mechanism in Artificial Immune Recognition System: Fuzzy Resource Allocation Mechanism and Application to Diagnosis of Atherosclerosis Disease , 2006, ICARIS.

[20]  Kemal Polat,et al.  Hepatitis disease diagnosis using a new hybrid system based on feature selection (FS) and artificial immune recognition system with fuzzy resource allocation , 2006, Digit. Signal Process..

[21]  Kemal Polat,et al.  A hybrid approach to medical decision support systems: Combining feature selection, fuzzy weighted pre-processing and AIRS , 2007, Comput. Methods Programs Biomed..

[22]  Kemal Polat,et al.  Breast cancer and liver disorders classification using artificial immune recognition system (AIRS) with performance evaluation by fuzzy resource allocation mechanism , 2007, Expert Syst. Appl..

[23]  Kemal Polat,et al.  Medical decision support system based on artificial immune recognition immune system (AIRS), fuzzy weighted pre-processing and feature selection , 2007, Expert Syst. Appl..

[24]  M. Neshat,et al.  Fuzzy Expert System Design for Diagnosis of Liver Disorders , 2008, 2008 International Symposium on Knowledge Acquisition and Modeling.

[25]  Ghumbre Shashikant Uttreshwar,et al.  Hepatitis B Diagnosis Using Logical Inference and Self-Organizing Map , 2008 .

[26]  Kourosh Mozafari,et al.  Hepatitis disease diagnosis using a novel hybrid method based on support vector machine and simulated annealing (SVM-SA) , 2012, Comput. Methods Programs Biomed..

[27]  F. Bagheri,et al.  Electrocardiogram (ECG) Signal Modeling and Noise Reduction Using Hopfield Neural Networks , 2013 .