作者
James WF Catto, Derek A Linkens, Maysam F Abbod, Minyou Chen, Julian L Burton, Kenneth M Feeley, Freddie C Hamdy
发表日期
2003/9/15
期刊
Clinical Cancer Research
卷号
9
期号
11
页码范围
4172-4177
出版商
American Association for Cancer Research
简介
Purpose: New techniques for the prediction of tumor behavior are needed, because statistical analysis has a poor accuracy and is not applicable to the individual. Artificial intelligence (AI) may provide these suitable methods. Whereas artificial neural networks (ANN), the best-studied form of AI, have been used successfully, its’ hidden networks remain an obstacle to its acceptance. Neuro-fuzzy modeling (NFM), another AI method, has a transparent functional layer and is without many of the drawbacks of ANN. We have compared the predictive accuracies of NFM, ANN, and traditional statistical methods, for the behavior of bladder cancer.
Experimental Design: Experimental molecular biomarkers, including p53 and the mismatch repair proteins, and conventional clinicopathological data were studied in a cohort of 109 patients with bladder cancer. For all three of the methods, models were …
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