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Applying Machine Learning Techniques to Analysis of Gene Expression Data: Cancer Diagnosis
[chapter]
2002
Methods of Microarray Data Analysis
Classification of patient samples is a crucial aspect of cancer diagnosis. DNA hybridization arrays simultaneously measure the expression levels of thousands of genes and it has been suggested that gene expression may provide the additional information needed to improve cancer classification and diagnosis. This paper presents methods for analyzing gene expression data to classify cancer types. Machine learning techniques, such as Bayesian networks, neural trees, and radial basis function (RBF)
doi:10.1007/978-1-4615-0873-1_13
fatcat:ftaxuah6qnfnvlzzpmj6nz75q4