UM
Clinical application of modified bag-of-features coupled with hybrid neural-based classifier in dengue fever classification using gene expression data
Chatterjee, Sankhadeep; Dey, Nilanjan; Shi, Fuqian; Ashour, Amira S.; Fong, Simon James; Sen, Soumya
2018-04
Source PublicationMEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
ISSN0140-0118
Volume56Issue:4Pages:709-720
AbstractDengue fever detection and classification have a vital role due to the recent outbreaks of different kinds of dengue fever. Recently, the advancement in the microarray technology can be employed for such classification process. Several studies have established that the gene selection phase takes a significant role in the classifier performance. Subsequently, the current study focused on detecting two different variations, namely, dengue fever (DF) and dengue hemorrhagic fever (DHF). A modified bag-of-features method has been proposed to select the most promising genes in the classification process. Afterward, a modified cuckoo search optimization algorithm has been engaged to support the artificial neural (ANN-MCS) to classify the unknown subjects into three different classes namely, DF, DHF, and another class containing convalescent and normal cases. The proposed method has been compared with other three well-known classifiers, namely, multilayer perceptron feed-forward network (MLP-FFN), artificial neural network (ANN) trained with cuckoo search (ANN-CS), and ANN trained with PSO (ANN-PSO). Experiments have been carried out with different number of clusters for the initial bag-of-features-based feature selection phase. After obtaining the reduced dataset, the hybrid ANN-MCS model has been employed for the classification process. The results have been compared in terms of the confusion matrix-based performance measuring metrics. The experimental results indicated a highly statistically significant improvement with the proposed classifier over the traditional ANN-CS model.
KeywordDengue fever Bag-of-features Modified cuckoo search Artificial neural networks Gene expression data Incremental feature selection scheme
DOI10.1007/s11517-017-1722-y
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering ; Mathematical & Computational Biology ; Medical Informatics
WOS SubjectComputer Science, Interdisciplinary Applications ; Engineering, Biomedical ; Mathematical & Computational Biology ; Medical Informatics
WOS IDWOS:000427851600014
PublisherSPRINGER HEIDELBERG
The Source to ArticleWOS
Fulltext Access
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Cited Times [WOS]:12   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionUniversity of Macau
Recommended Citation
GB/T 7714
Chatterjee, Sankhadeep,Dey, Nilanjan,Shi, Fuqian,et al. Clinical application of modified bag-of-features coupled with hybrid neural-based classifier in dengue fever classification using gene expression data[J]. MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING,2018,56(4):709-720.
APA Chatterjee, Sankhadeep,Dey, Nilanjan,Shi, Fuqian,Ashour, Amira S.,Fong, Simon James,&Sen, Soumya.(2018).Clinical application of modified bag-of-features coupled with hybrid neural-based classifier in dengue fever classification using gene expression data.MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING,56(4),709-720.
MLA Chatterjee, Sankhadeep,et al."Clinical application of modified bag-of-features coupled with hybrid neural-based classifier in dengue fever classification using gene expression data".MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING 56.4(2018):709-720.
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