Lung cancer classification tool using microarray data and support vector machines

Abstract

Lung cancer is one of the deadliest types of cancer around the world. Epidemiologic studies have shown that genetic variability is among the factors that affect a person's susceptibility to lung cancer. A recent study conducted by a team of researchers from the United States National Cancer Institute among 14,000 Asian women found out that Asian women, whether smokers or not, are more prone to developing cancer due to their genetic variations. This study proposes a system that utilizes gene expression data from oligonucleotide microarrays 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.