The precise diagnosis of cancer type based on microarray data is of particular importance and is alsoa challenging task. We have devised a novel pattern recognition procedure based on independentcomponent analysis (ICA). Different from the conventional cancer classification methods, which are limitedin their clinical applicability of cancer diagnosis, our method extracts explicitly, by ICA algorithm, a set ofspecific diagnostic patterns of normal and tumor tissues corresponding to a set of biomarkers for clinicaluse. We validated our procedure with the colon and prostate cancer data sets and achieved good diagnosis(490%) on the data sets studied here. This technique is also suitable for the identification of diagnosticexpression patterns for other human cancers and demonstrates the feasibility of simple and accuratemolecular cancer diagnostics for clinical implementation.