MICROARRAY GENE BASED DISEASE PREDICTION USING PATTERN SIMILARITY BASED SVM CLASSIFICATION
Santhakumar D
, Dr.S.Logeswari
Bio-medical research, DNA microarray, Gene sequence, Clustering, Classification
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.
"MICROARRAY GENE BASED DISEASE PREDICTION USING PATTERN SIMILARITY BASED SVM CLASSIFICATION", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.4, Issue 12, page no.67 - 71, December-2019, Available :https://ijsdr.org/papers/IJSDR1912016.pdf
Volume 4
Issue 12,
December-2019
Pages : 67 - 71
Paper Reg. ID: IJSDR_191147
Published Paper Id: IJSDR1912016
Downloads: 000347390
Research Area: Engineering
Country: Cuddalore, Tamilnadu, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
