Lung Cancer Classification Tool Using Microarray Data and Support Vector Machines

dc.contributor.advisor	Solano, Geoffrey S.
dc.contributor.author	Cabrera, Jennifer P.
dc.date.accessioned	2015-07-24T11:47:43Z
dc.date.available	2015-07-24T11:47:43Z
dc.date.issued	2014-04
dc.identifier.uri	http://cas.upm.edu.ph:8080/xmlui/handle/123456789/31
dc.description.abstract	Lung cancer is one of the deadliest types of cancer in country and around the world. Epidemiologic studies have shown that genetic variability is among the factors that affect a person’s susceptibility to lung cancer. This study proposes a system that will utilize gene expression data to predict the presence or absence of lung cancer, predict the specific type of lung cancer should it be present, and determine marker genes that are attributable to the specific kind of the disease. The proposed system would help in the faster diagnosis and serve as a reliable adjunct approach to current lung cancer classification methods.	en_US
dc.language.iso	en	en_US
dc.subject	lung cancer diagnosis	en_US
dc.subject	lung cancer classification	en_US
dc.subject	support vector machines	en_US
dc.subject	microarray gene expression data	en_US
dc.subject	preprocessing and feature selection techniques	en_US
dc.title	Lung Cancer Classification Tool Using Microarray Data and Support Vector Machines	en_US
dc.type	Thesis	en_US