Data mining with combined use of optimization techniques and self-organizing maps for improving risk grouping rules : Application to prostate cancer patients
Local optimization method with global multidimensional search
Supervised data classification via max-min separability
Improving risk grouping rules for prostate cancer patients with optimization
Comparative analysis of the cutting angle and simulated annealing methods in global optimization
New algorithms for multi-class cancer diagnosis using tumor gene expression signatures
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