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Staging of Prostate Cancer Using Automatic Feature Selection, Sampling and Dempster-Shafer Fusion
A novel technique of automatically selecting the best pairs of features and sampling techniques to predict the stage of prostate cancer is proposed in this study. The problem of class imbalance, which is prominent in most medical data sets is also addressed here. Three feature subsets obtained by th...
| Autores principales: | , , |
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| Formato: | Texto |
| Lenguaje: | English |
| Publicado: |
Libertas Academica
2009
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2664701/ https://www.ncbi.nlm.nih.gov/pubmed/19352459 |