Cell-nuclear data reduction and prognostic model selection in bladder tumor recurrence

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摘要

ObjectiveThe paper aims at improving the prediction of superficial bladder recurrence. To this end, feedforward neural networks (FNNs) and a feature selection method based on unsupervised clustering, were employed.

论文关键词：Prognosis of cancer recurrence,Neural networks,Unsupervised clustering,Feature selection

论文评审过程：Received 5 September 2005, Revised 24 July 2006, Accepted 25 July 2006, Available online 27 September 2006.

论文官网地址：https://doi.org/10.1016/j.artmed.2006.07.008