Evaluation of artificial neural networks for the prediction of pathologic stage in prostate carcinoma

Currently, the standard for predicting pathologic stage from information available at the time of prostate biopsy is the “Partin nomograms” that were derived using logistic regression analysis. The authors retrospectively reviewed a large series of men with clinically localized prostate carcinoma who underwent staging pelvic lymphadenectomy and radical retropubic prostatectomy. They then utilized pathologic and clinical data at the time of prostate biopsy to develop and test an artificial neural network (ANN) to predict the final pathologic stage for this group of men. They then compared the results of ANN with the previous nomograms.

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