Journal ArticleDOI
Clinical application of modified bag-of-features coupled with hybrid neural-based classifier in dengue fever classification using gene expression data
Reads0
Chats0
TLDR
A modified bag-of-features method has been proposed to select the most promising genes in the classification process and results indicated a highly statistically significant improvement with the proposed classifier over the traditional ANN-CS model.Abstract:
Dengue 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.read more
Citations
More filters
Journal ArticleDOI
Evaluation of Recurrent Neural Network and its Variants for Intrusion Detection System (IDS)
TL;DR: This article describes how howSequences areﻷ attributedﻴtemporal�characteristicsﻵeitherﻰ�explicitlyﻡ�orﻢimplicitly £2.5m Cybersecurity.
Journal ArticleDOI
Severe Dengue Prognosis Using Human Genome Data and Machine Learning
Caio Davi,André Filipe Pastor,Thiego Oliveira,Fernando Buarque de Lima Neto,Ulisses Braga-Neto,Abigail W. Bigham,Michael J. Bamshad,Ernesto T. A. Marques,Bartolomeu Acioli-Santos +8 more
TL;DR: The proposed classification method can be used to identify individuals at high risk for developing the severe dengue phenotype even in uninfected conditions and is extendable to other Mendelian based and genetically influenced diseases.
Journal ArticleDOI
Nature-inspired algorithms for feed-forward neural network classifiers: A survey of one decade of research
Ashraf Mohamed Hemeida,Somaia Awad Hassan,Al-Attar Ali Mohamed,Salem Alkhalaf,Mountasser M.M. Mahmoud,Tomonobu Senjyu,Ayman M. Bahaa Eldin +6 more
TL;DR: This study provides a review on the basic theories and main recent algorithms for optimizing the ANN, and different types of nature-inspired meta-heuristic algorithms are presented; outlining the concepts and components that are used in order to give a summary and ease of the state-of-the-arts to find suitable methods in real world applications for the readers.
Journal ArticleDOI
Soil moisture quantity prediction using optimized neural supported model for sustainable agricultural applications
TL;DR: A modified Flower Pollination Algorithm has been employed to train Artificial Neural Network to predict soil moisture quantity and the proposed method is compared with well known PSO supported ANN and Cuckoo Search supported ANN along with MLP-FFN classifier.
Journal ArticleDOI
Adaptive Cuckoo Search based optimal bilateral filtering for denoising of satellite images.
Anju Asokan,J. Anitha +1 more
TL;DR: The proposed Adaptive Cuckoo Search based bilateral filter denoising gives better results in terms of Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), Feature Similarity Index (FSIM), Entropy and CPU time in comparison to traditional methods such as Median filter and RGB spatial filter.
References
More filters
Journal ArticleDOI
Molecular classification of cancer: class discovery and class prediction by gene expression monitoring.
Todd R. Golub,Todd R. Golub,Donna K. Slonim,Pablo Tamayo,Christine Huard,Michelle Gaasenbeek,Jill P. Mesirov,Hilary A. Coller,Mignon L. Loh,James R. Downing,Michael A. Caligiuri,Clara D. Bloomfield,Eric S. Lander +12 more
TL;DR: A generic approach to cancer classification based on gene expression monitoring by DNA microarrays is described and applied to human acute leukemias as a test case and suggests a general strategy for discovering and predicting cancer classes for other types of cancer, independent of previous biological knowledge.
Journal ArticleDOI
The global distribution and burden of dengue
Samir Bhatt,Peter W. Gething,Oliver J. Brady,Jane P. Messina,Andrew Farlow,Catherine L. Moyes,John M. Drake,John M. Drake,John S. Brownstein,Anne G. Hoen,Osman Sankoh,Osman Sankoh,Monica F. Myers,Dylan B. George,Thomas Jaenisch,G. R. William Wint,Cameron P. Simmons,Thomas W. Scott,Thomas W. Scott,Jeremy Farrar,Jeremy Farrar,Simon I. Hay,Simon I. Hay +22 more
TL;DR: These new risk maps and infection estimates provide novel insights into the global, regional and national public health burden imposed by dengue and will help to guide improvements in disease control strategies using vaccine, drug and vector control methods, and in their economic evaluation.
Journal ArticleDOI
Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays.
Uri Alon,Naama Barkai,Daniel A. Notterman,Kurt C. Gish,S. Ybarra,David H. Mack,A. J. Levine,A. J. Levine +7 more
TL;DR: In this paper, a two-way clustering algorithm was applied to both the genes and the tissues, revealing broad coherent patterns that suggest a high degree of organization underlying gene expression in these tissues.
Journal ArticleDOI
Original Contribution: A scaled conjugate gradient algorithm for fast supervised learning
TL;DR: Experiments show that SCG is considerably faster than BP, CGL, and BFGS, and avoids a time consuming line search.
Journal ArticleDOI
Use of proteomic patterns in serum to identify ovarian cancer
Emanuel F. Petricoin,Ali M. Ardekani,Ben A. Hitt,Peter J. Levine,Vincent A. Fusaro,Seth M. Steinberg,Gordon B. Mills,Charles B. Simone,David A. Fishman,Elise C. Kohn,Lance A. Liotta +10 more
TL;DR: A bioinformatics tool was developed and used to identify proteomic patterns in serum that distinguish neoplastic from non-neoplastic disease within the ovary, justifying a prospective population-based assessment of proteomic pattern technology as a screening tool for all stages of ovarian cancer in high-risk and general populations.