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Momentum Backpropagation Optimization for Cancer Detection Based on DNA Microarray Data

Untari Novia Wisesty, Febryanti Sthevanie, Rita Rismala
2021 International Journal of Artificial Intelligence Research  
Early detection of cancer can increase the success of treatment in patients with cancer. In the latest research, cancer can be detected through DNA Microarrays.  ...  The proposed scheme can gain high accuracy of 90.51% for Colon Tumor data, and 100% for Leukemia, Lung Cancer, and Ovarian Cancer data.  ...  The following pseudo code (Table 1 ) describes the stages of a cancer detection system based on DNA microarray data.  ... 
doi:10.29099/ijair.v4i2.188 fatcat:simadhkdurcphnqmexzohvivye

Cancer prediction using graph-based gene selection and explainable classifier

Mehrdad Rostami, Mourad Oussalah
2022 Finnish Journal of eHealth and eWelfare  
In this study, an efficient and effective model is developed for gene selection and cancer prediction.  ...  In contrast to previous deep learning-based cancer prediction models, which are difficult to explain to physicians due to their black-box nature, the proposed prediction model is based on a transparent  ...  With the developed gene selection strategy, not only will the most redundant genes be selected, but also their relevance to DNA microarray cancer data will be maximized.  ... 
doi:10.23996/fjhw.111772 fatcat:paqhmluzuzcbhc2suexkmofmva

'Gene Micro Array Content Extraction' An Application Approach Using LFDA, SVM, and Cluster Classification

Thomas Scaria, Christopher T, Gifty Stephen
2017 International Journal of Engineering and Technology  
The DNA microarray technology enables the biologists to observe the expressions of multiple thousands of genes in parallel fashion.  ...  This step is then followed by the classification of gene information with respect to the user's requirement. After that of classification we try to form gene clusters.  ...  that deals with microarray gene data.  ... 
doi:10.21817/ijet/2017/v9i2/170902160 fatcat:arq3qruwtnc7tjmxyjv3h6mkra

Building an Ensemble Feature Selection Approach for Cancer Microarray Datasets Using Different Classifiers

Sabah Sayed, Cairo University, Mohammad Nassef, Amr Badr, Ibrahim Farag, Cairo University, Cairo University, Cairo University
2019 International Journal of Intelligent Engineering and Systems  
The proposed approach has been applied on two different datasets for Lung cancer; Microarray Gene Expression and DNA methylation datasets aiming to find the Lung cancer biomarker genes.  ...  This study presents an ensemble feature selection approach based on t-test and Genetic Algorithm with five different classification algorithms as its fitness function: Support Vector Machine, Random Forest  ...  An ensemble-based feature selection technique was proposed in [24] to classify the Lung cancer subtypes based on DNAm data only.  ... 
doi:10.22266/ijies2019.0831.06 fatcat:az4r6wcr5fgptoetry5ugzu6qa

Integrative Gene Selection for Classification of Microarray Data

Huey Fang Ong, Norwati Mustapha, Md. Nasir Sulaiman
2011 Computer and Information Science  
This paper presents an integrative gene selection for improving microarray data classification performance.  ...  Microarray data classification is one of the major interests in health informatics that aims at discovering hidden patterns in gene expression profiles.  ...  Moreover the experiments show that KEGG pathways are suitable to be integrated with microarray data for identifying gene markers for cancer classification purpose.  ... 
doi:10.5539/cis.v4n2p55 fatcat:apiwk4sacbfqvpoezibmqkmxve

DNA Microarrays Are Predictive of Cancer Prognosis: A Re-evaluation

X. Fan, L. Shi, H. Fang, Y. Cheng, R. Perkins, W. Tong
2010 Clinical Cancer Research  
We set to investigate the reality of microarrays for predicting cancer prognosis by using the same data sets with commonly accepted data analysis approaches. Experiment Design: Michiels et al.'  ...  Conclusions: We concluded that the use of DNA microarrays for cancer prognosis can be demonstrated.  ...  This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.  ... 
doi:10.1158/1078-0432.ccr-09-1815 pmid:20068095 fatcat:kxec6yp535ejbdfyh6bkh5jdqq

Gene boosting for cancer classification based on gene expression profiles

Jin-Hyuk Hong, Sung-Bae Cho
2009 Pattern Recognition  
Gene selection is one of the important issues for cancer classification based on gene expression profiles.  ...  It repeatedly selects a set of top-ranked informative genes by a filtering algorithm with respect to a temporal training dataset constructed according to the classification result for the original training  ...  In many studies on cancer classification using microarray data, filter approaches have been widely investigated. Lee et al.  ... 
doi:10.1016/j.patcog.2009.01.006 fatcat:5lsvfva35rganobjzxb5mqzepa


Farzana Kabir Ahmad
2016 Jurnal Teknologi  
These gene selection methods are tested on three large scales of gene expression datasets, namely breast cancer dataset, colon dataset, and lung dataset.  ...  Although filter based gene selection techniques have been commonly used in analyzing microarray dataset, these techniques have been tested separately in different studies.  ...  Consequently, the development of the high-throughput technologies such as DNA microarray has led to incremental growth in the secondary datasets.  ... 
doi:10.11113/jt.v78.8843 fatcat:kv44eunb4bgkhpovq2vchi7iny

A Survey on Probabilistic Computational Model for Microarray Data Classification

Barnali Sahu, Ishara Priyadarsani
2017 International Journal of Advanced Research in Computer Science and Software Engineering  
Probabilistic classifiers have received relatively little attention in the literature of less number of sample sizes and a large number of gene sizes in microarray data and microarray data exhibit a high  ...  Fig. 3 Classification accuracy for different microarray data set VII.  ...  Based on the study of gene expression microarray data appropriate probabilistic classification is much more complicated than deterministic classification [24] .  ... 
doi:10.23956/ijarcsse/sv7i5/0221 fatcat:77ctmx7xg5hqhl5ca55ztleadm

Swarm Intelligence Algorithms in Gene Selection Profile Based on Classification of Microarray Data: A Review

Alan Jahwar, Nawzat Ahmed
2021 Journal of Applied Science and Technology Trends  
A review on swarm intelligence algorithms in gene selection profile based on classification of Microarray Data is presented in this paper.  ...  Microarray data plays a major role in diagnosing and treating cancer. In several microarray data sets, many gene fragments are not associated with the target diseases.  ...  Profiles on gene expression may provide more details on accurate classification from cancer samples.  ... 
doi:10.38094/jastt20161 fatcat:xdjnq4anjjcz3jc33e6wecotya

The classification of cancer based on DNA microarray data that uses diverse ensemble genetic programming

Jin-Hyuk Hong, Sung-Bae Cho
2006 Artificial Intelligence in Medicine  
Object: The classification of cancer based on gene expression data is one of the most important procedures in bioinformatics.  ...  In order to obtain highly accurate results, ensemble approaches have been applied when classifying DNA microarray data.  ...  Since the proposed method classifies samples with a linear boundary The classification of cancer based on DNA microarray 51 The relationship between the number of base classification rules and the performance  ... 
doi:10.1016/j.artmed.2005.06.002 pmid:16102956 fatcat:n2v6norbsfbkneaydxaymwgbou

A microarray gene expressions with classification using extreme learning machine

M. Yasodha, P. Ponmuthuramalingam
2015 Genetika  
Ponmuthuramalingam (2015): A microarray gene expressions with classification using extreme learning machine.  ...  In cancer diagnosis and molecular biology, a utilized effective tool is DNA microarrays.  ...  It is observed that the algorithm finds a small gene subset that provides high classification accuracy on several DNA microarray gene expression data sets.  ... 
doi:10.2298/gensr1502523y fatcat:pkcdzl6t6ngonki3dmr2brfo2i

An Efficient Feature Selection Strategy Based on Multiple Support Vector Machine Technology with Gene Expression Data

Ying Zhang, Qingchun Deng, Wenbin Liang, Xianchun Zou
2018 BioMed Research International  
In order to select determinant genes related to breast cancer from the initial gene expression data, we propose a new feature selection method, namely, support vector machine based on recursive feature  ...  The application of gene expression data to the diagnosis and classification of cancer has become a hot issue in the field of cancer classification.  ...  Supplementary Materials The supplementary materials contain the files of GEO data set and TCGA data set used in the experiment, as well as the main code files used in the experiment.  ... 
doi:10.1155/2018/7538204 pmid:30228989 pmcid:PMC6136508 fatcat:aft5c5ixb5c4zfpthla42zhpne

Boolean Rule Based Classification for Microarray Gene Expression Data

2019 International journal of recent technology and engineering  
To analyze and classify the gene expression data is more complex task. The rule based classifications are used to simplify the task of classifying genes.  ...  Microarray technology provides a way to identify the expression level of ten thousands of genes simultaneously. This is useful for prediction and decision for the cancer treatments.  ...  The test data of any one attribute is present and covers the rules the corresponding class label count is incremented.  ... 
doi:10.35940/ijrte.c6100.098319 fatcat:tfnuqq36abfxtikqowq75e57ri

Prediction of high-risk patients by genome-wide copy number alterations from remaining cancer after neoadjuvant chemotherapy and surgery

2009 International Journal of Oncology  
In breast cancer, changes of gene copy number were analyzed by cDNA microarray-based comparative genome hybridization using post-treatment archived tissues.  ...  Informative genes were selected by t-test and were statistically validated by prediction analysis using support vector machine in R package.  ...  The data were presented at the 40th Annual Meeting of American Society of Clinical Oncology at New Orleans, LA, June [5] [6] [7] [8] 2004.  ... 
doi:10.3892/ijo_00000210 fatcat:wfxvoyqc75fwtnzmqopw45dguu
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