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: | , , , , , , , |
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| Format: | Article |
| Language: | English English |
| Published: |
Czech Technical University in Prague, Faculty of Transportation Sciences
2015
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| Subjects: | |
| 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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