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Abstract: The application of artificial neural networks (ANNs) for prognostic and diagnostic classification in clinical medicine has become very popular. Some indications might be derived from a recent "mini-series" in the Lancet 7,23,30,94 with three more or less enthusiastic review articles and an additional commentary expressing at least some scepticism. In this paper, the essentials of feed-forward neural networks and their statistical counterparts (e.g. logistic regression models) are reviewed. We ... (Update)
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.... manually in a non blinded way to the test data, or by examining in a blinded fashion too many models using automated search procedures) [7,15]. To what extend are the reported results in microarray analysis an artifact of the evaluation methodologies employed What methods...
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BibTeX entry: (Update)
Schwarzer G, Vach W, On the misuses of artificial neural networks for prognostic and diagnostic classification in oncology. Stat Med. 2000 Feb 29;19(4):541-61. http://citeseer.ist.psu.edu/schwarzer00misuses.html More
@misc{ schwarzer00misuses,
author = "G. Schwarzer and W. Vach",
title = "the misuses of artificial neural networks for prognostic and diagnostic
classification in oncology",
text = "Schwarzer G, Vach W, On the misuses of artificial neural networks for prognostic
and diagnostic classification in oncology. Stat Med. 2000 Feb 29;19(4):541-61.",
year = "2000",
url = "citeseer.ist.psu.edu/schwarzer00misuses.html" }
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