Loading...
Please wait, while we are loading the content...
Similar Documents
Prognostic Value of Histology and Lymph Node Status in Bilharziasis-bladder Cancer : Outcome Prediction Using Neural Networks
| Content Provider | Semantic Scholar |
|---|---|
| Author | Ji, Wen-Bin Naguib, Raouf N. G. Petrović, Davor Gaura, Elena Ghoneim, Mohammed Abd-Elfttah |
| Copyright Year | 2001 |
| 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. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.dtic.mil/get-tr-doc/pdf?AD=ADA412467 |
| Alternate Webpage(s) | http://www.dtic.mil/dtic/tr/fulltext/u2/a412467.pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Anatomic Node Biological Neural Networks Bladder Neoplasm Extraction Forecast of outcome IBM Security Directory Server Lymph Node Tissue Lymphadenopathy MTA SZTAKI Laboratory of Parallel and Distributed Systems Neoplasms Operational data store Patients Prognostic variable Radial basis function Schistosomiasis Subgroup lymph nodes |
| Content Type | Text |
| Resource Type | Article |
