International Journal of Scientific Development and Research - IJSDR
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Authors Name: Santhakumar D , Dr.S.Logeswari
Unique Id: IJSDR1912016
Published In: Volume 4 Issue 12, December-2019
Abstract: The DNA microarray technology has modernized the approach of biology research in such a way that scientists can now measure the expression levels of thousands of genes simultaneously in a single experiment. Gene expression profiles, which represent the state of a cell at a molecular level, have great potential as a medical diagnosis tool. Diseases classification with gene expression data is known to include the keys for addressing the fundamental harms relating to diagnosis and discovery. The recent introduction of DNA microarray technique has complete simultaneous monitoring large number of gene expressions possible. With this large quantity of gene expression data, experts have started to discover the possibilities of disease classification using gene expression data. Quite a large number of methods have been planned in recent years with hopeful results. But there are still a set of issues which need to be address and understood. In order to gain insight into the disease classification difficulty, it is necessary to get a closer look at the problem, the proposed solutions and the associated issues all together. In this project, we present a comprehensive clustering method and classification method such as Particle Swarm Optimization (PSO), K-NN classification algorithm and estimate them based on their evaluation time, classification accuracy and ability to reveal biologically meaningful gene information. Based on our multiclass classification method to diagnosis the diseases and also find severity levels of diseases. Our experimental results show that classifier performance through graphs with improved accuracy.
Keywords: Bio-medical research, DNA microarray, Gene sequence, Clustering, Classification
Cite Article: "MICROARRAY GENE BASED DISEASE PREDICTION USING PATTERN SIMILARITY BASED SVM CLASSIFICATION", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.4, Issue 12, page no.67 - 71, December-2019, Available :http://www.ijsdr.org/papers/IJSDR1912016.pdf
Downloads: 00060116
Publication Details: Published Paper ID: IJSDR1912016
Registration ID:191147
Published In: Volume 4 Issue 12, December-2019
DOI (Digital Object Identifier):
Page No: 67 - 71
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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