A Genetic-Neural System Diagnosing Hepatitis B

A Genetic-Neural System Diagnosing Hepatitis B

E. Areghan

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S. Konyeha

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University of Benin

A Genetic-Neural System Diagnosing Hepatitis B

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Abstract

Hepatitis B is a life threaten disease and if not diagnose early can lead to death of the infected patient. In this paper a genetic neural system for diagnosing hepatitis B was designed. The system was designed to diagnose HBV using clinical symptoms. The dataset used in training the system was gotten from UCI repository. The system incorporated both genetic algorithm and neural network. The genetic algorithm was used to optimize the dataset used in training the neural network. The neural network was trained for 300 iterations and the system had a prediction accuracy of 99.14% on predicting Hepatitis B.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

E. Areghan. 2019. \u201cA Genetic-Neural System Diagnosing Hepatitis B\u201d. Global Journal of Computer Science and Technology - D: Neural & AI GJCST-D Volume 19 (GJCST Volume 19 Issue D3): .

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GJCST Volume 19 Issue D3
Pg. 1- 6

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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Classification

GJCST-D Classification: C.1.3

Submission ReceivedDecember 13, 2018
Peer Review Double Blind
Handling Editor
Accepted January 4, 2019
Published January 15, 2019

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v1.2

Issue date

July 17, 2019

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