Cancer classification based on gene expression using neural networks

Genetics and Molecular Research : GMR
H P HuX H Tan

Abstract

Based on gene expression, we have classified 53 colon cancer patients with UICC II into two groups: relapse and no relapse. Samples were taken from each patient, and gene information was extracted. Of the 53 samples examined, 500 genes were considered proper through analyses by S-Kohonen, BP, and SVM neural networks. Classification accuracy obtained by S-Kohonen neural network reaches 91%, which was more accurate than classification by BP and SVM neural networks. The results show that S-Kohonen neural network is more plausible for classification and has a certain feasibility and validity as compared with BP and SVM neural networks.

Citations

Dec 16, 2016·Journal of Chromatography. B, Analytical Technologies in the Biomedical and Life Sciences·Xiye WangLiang Xu
Mar 11, 2020·Cancer Medicine·Carlo BoeriFrancesca Rovera
Jan 26, 2020·Artificial Intelligence in Medicine·Ivan LorencinZlatan Car
May 1, 2021·Current Oncology·Athanasia MitsalaAlexandra K Tsaroucha

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