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Momentum Backpropagation Optimization for Cancer Detection Based on DNA Microarray Data
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
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
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
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
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
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
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
A COMPARATIVE STUDY ON GENE SELECTION METHODS FOR TISSUES CLASSIFICATION ON LARGE SCALE GENE EXPRESSION DATA
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
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
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
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
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
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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