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Its performance was compared in cross validation with that of standard supervised methods, namely: decision tree, artificial neural network, support vector machine (SVM) and<jats:italic>k<\/jats:italic>-nearest neighbor classifier.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>LLM showed an excellent accuracy (<jats:italic>sAUC<\/jats:italic>\u2009=\u20090.99, 95%<jats:italic>CI<\/jats:italic>: 0.98\u20131.0) and outperformed any other method except SVM.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>LLM is a new powerful tool for the analysis of gene expression data for cancer diagnosis. 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