Lung Cancer Classification Tool Using Microarray Data and Support Vector Machines

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.