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

Doğantekin, Esin; Doğantekin, Akif; Avcı, Derya

doi:10.1016/j.eswa.2009.03.021

Cited by 57 publications

(39 citation statements)

References 15 publications

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“…ANN based model summary is represented in Table 4 giving the value of cross entropy error and percentage of erroneous predictions along with the training time. Table 5 represents classification accuracy in percentage of nineteen different methods which were used for the diagnosis of hepatitis virus and our proposed method [27].…”

Section: Back Propagation Algorithmmentioning

confidence: 99%

PCA-ANN for Classification of Hepatitis-C Patients

Jilani¹,

Yasin²,

Yasin³

2011

IJCA

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In this paper, an automatic diagnosis system based on Neural Network for hepatitis virus is introduced. This automatic diagnosis system deals with the mixture of feature extraction and classification. The system has two stages, which are feature extraction -reduction and classification stages. In the feature extraction -diminution stage, the hepatitis features were obtained from UCI Repository of Machine Learning Databases. Missing values of the instances are adjusted using local mean method. Then, the number of these features was reduced to 6 from 19 due to relative significance of fields. In the classification stage, these reduced features are given as inputs Neural Network classifier. The classification accuracy of this ANN diagnosis system for the diagnosis of hepatitis virus was obtained, this accuracy was around 99.1% for training data and 100% for testing data.

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Section: Back Propagation Algorithmmentioning

confidence: 99%

PCA-ANN for Classification of Hepatitis-C Patients

Jilani¹,

Yasin²,

Yasin³

2011

IJCA

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“…Hepatitis-A mainly infects by fecal contaminated substances taken by mouth. As a result of poor hygienic conditions, this results in epidemics based on water or food, especially in developing countries [1]. In infection of hepatitis A, any indication may be observed.…”

Section: Introductionmentioning

confidence: 99%

“…Viral hepatitis refers to several common contagious diseases caused by viruses that attack the liver. The most important types of viral hepatitis are hepatitis-A, hepatitis-B, and hepatitis-C [2]. New forms of viral hepatitis such as D, E and G are also discovered.…”

Section: Introductionmentioning

confidence: 99%

“…The hepatitis can be acute or chronic and it is a common disease over the world. The different types of hepatitis are caused by different things, but they all produce inflammation of the liver [1]. Viral hepatitis refers to several common contagious diseases caused by viruses that attack the liver.…”

Section: Introductionmentioning

confidence: 99%

“…Non-viral forms of hepatitis can be caused by toxic agents (drugs or chemicals), alcohol, or autoimmune processes. Another form of hepatitis is toxic hepatitis [1].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An Automatic Diagnosis System for Hepatitis Diseases Based on Genetic Wavelet Kernel Extreme Learning Machine

Avcı¹

2016

Journal of Electrical Engineering and Technology

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-Hepatitis is a major public health problem all around the world. This paper proposes an automatic disease diagnosis system for hepatitis based on Genetic Algorithm (GA) Wavelet Kernel (WK) Extreme Learning Machines (ELM). The classifier used in this paper is single layer neural network (SLNN) and it is trained by ELM learning method. The hepatitis disease datasets are obtained from UCI machine learning database. In Wavelet Kernel Extreme Learning Machine (WK-ELM) structure, there are three adjustable parameters of wavelet kernel. These parameters and the numbers of hidden neurons play a major role in the performance of ELM. Therefore, values of these parameters and numbers of hidden neurons should be tuned carefully based on the solved problem. In this study, the optimum values of these parameters and the numbers of hidden neurons of ELM were obtained by using Genetic Algorithm (GA). The performance of proposed GA-WK-ELM method is evaluated using statical methods such as classification accuracy, sensitivity and specivity analysis and ROC curves. The results of the proposed GA-WK-ELM method are compared with the results of the previous hepatitis disease studies using same database as well as different database. When previous studies are investigated, it is clearly seen that the high classification accuracies have been obtained in case of reducing the feature vector to low dimension. However, proposed GA-WK-ELM method gives satisfactory results without reducing the feature vector. The calculated highest classification accuracy of proposed GA-WK-ELM method is found as 96.642 %.

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Spatial Prediction of Rainfall Induced Shallow Landslides Using Adaptive-Network-Based Fuzzy Inference System and Particle Swarm Optimization: A Case Study at the Uttarakhand Area, India

Pham

Prakash

2017

Advances and Applications in Geospatial Technology and Earth Resources

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

Cited by 57 publications

References 15 publications

PCA-ANN for Classification of Hepatitis-C Patients

PCA-ANN for Classification of Hepatitis-C Patients

An Automatic Diagnosis System for Hepatitis Diseases Based on Genetic Wavelet Kernel Extreme Learning Machine

Spatial Prediction of Rainfall Induced Shallow Landslides Using Adaptive-Network-Based Fuzzy Inference System and Particle Swarm Optimization: A Case Study at the Uttarakhand Area, India

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