@inproceedings{c45e5b7de14242d797385b4046d5d3d5,
title = "Prognostic value of histology and lymph node status in bilharziasis-bladder cancer: Outcome prediction using neural networks",
abstract = "In this paper, the evaluation of two features in predicting the outcomes of patients with bilharziasis bladder cancer has been investigated using an RBF neural network. Prior to prediction, the feature subsets were extracted from the whole set of features for the purpose of providing a high performance of the network. Throughout the analysis of the prognostic feature combinations, two features, histological type and lymph node status, have been identified as the important indicators for outcome prediction of this type of cancer. The highest predictive accuracy reached 85.0% in this study.",
keywords = "Schistosomiasis, feature extraction, classification, survival analysis, epidemiology, SURVIVAL, STAGE",
author = "Wei Ji and Naguib, {Raouf N. G.} and Dobrila Petrovic and Elena Gaura and Ghoneim, {M. A.}",
year = "2001",
doi = "10.1109/IEMBS.2001.1019685",
language = "English",
isbn = "0780372115",
series = "Proceedings of Annual International Conference of the IEEE Engineering In Medicine and Biology Society",
publisher = "Institute of Electrical and Electronics Engineers (IEEE)",
pages = "3870--3873",
booktitle = "Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Vols 1-4",
address = "United States",
note = "23rd Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society ; Conference date: 25-10-2001 Through 28-10-2001",
}