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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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Bibliographic Details
Main Authors: Haruna, Chiroma, Abdul kareem, Sameem, Umar, Ibrahim, Ahmad, Gadam, Abdulmumini , Garba, Abubakar, Adamu, Fatihu, Mukhtar, Herawan, Tutut
Format: Article
Language:English
English
Published: Czech Technical University in Prague, Faculty of Transportation Sciences 2015
Subjects:
Z665 Library Science. Information Science
Online Access: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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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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