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Malaria severity classification through Jordan-Elman neural network based on features extracted from thick blood smear

This article presents an alternative approach useful for medical prac- titioners who wish to detect malaria and accurately identify the level of severity. Malaria classifiers are usually based on feed forward neural networks. In this study, the proposed classifier is developed based on the Jordan...

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Main Authors:	Haruna, Chiroma, Abdul kareem, Sameem, Umar, Ibrahim, Ahmad, Gadam, Abdulmumini , Garba, Abubakar, Adamu, Fatihu, Mukhtar, Herawan, Tutut
格式:	Article
语言:	English English
出版:	Czech Technical University in Prague, Faculty of Transportation Sciences 2015
主题:	Z665 Library Science. Information Science
在线阅读:	http://irep.iium.edu.my/46647/1/NNW.2015.25.028.pdf http://irep.iium.edu.my/46647/4/46647_Malaria_severity_classification_through_Jordan-Elman_neural_network_WOS.pdf http://irep.iium.edu.my/46647/ http://khis.khu.ac.kr:9090/SummonRecord/FETCH-LOGICAL-p521-5050a2458441821306734c03fd8ca088b3a9662fe6f3e363cee8675633ac83f43
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Malaria severity classification through Jordan-Elman neural network based on features extracted from thick blood smear

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