Prediction of stone disease by discriminant analysis and artificial neural networks in genetic polymorphisms: a new method.

Abstract excerpt

OBJECTIVE: To use information from genetic polymorphisms and from patients (drinking/exercise habits) to identify their association with stone disease, the main analytical and predictive tools being discriminant analysis (DA) and artificial neural networks (ANNs). PATIENTS, SUBJECTS AND METHODS: Urinary stone disease is common in Taiwan; the formation of calcium oxalate stone is reportedly associated with genetic...

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