Neural network analysis of clinicopathological factors in urological disease: a critical evaluation of available techniques-Reference-Cited by-同舟云学术

Neural network analysis of clinicopathological factors in urological disease: a critical evaluation of available techniques

Published:2001-11 Issue:8 Volume:88 Page:825-831
ISSN:1464-4096
Container-title:BJU International
language:en
Short-container-title:

Author:

Finne P.,Finne R.,Stenman U.-H.

Publisher

Wiley

Subject

Urology

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1046/j.1464-4096.2001.02461.x/fullpdf

Reference28 articles.

1. Artificial neural networks in the diagnosis and prognosis of prostate cancer: a pilot study;Snow;J Urol,1994

2. Gomari M Finne P Järvi T Stenman U-H Hugosson J Learning vector quantization, multilayer perceptron, neurofuzzy network and logistic regression in the diagnosis of prostate cancer Proceedings of the 1998 International Conference on Parallel and Distributed Processing Techniques and Applications 1998 : 516 25

3. Estimation of prostate cancer probability by logistic regression: free and total prostate-specific antigen, digital rectal examination, and heredity are significant variables;Virtanen;Clin Chem,1999

4. Predicting the outcome of prostate biopsy in screen-positive men by a multilayer perceptron network;Finne;Urology,2000

5. A probabilistic model for information storage and organization in the brain;Rosenblatt;Psychol Rev,1958

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