Classification models for early detection of prostate cancer.
We investigate the performance of different classification models and their ability to recognize prostate cancer in an early stage. We build ensembles of classification models in order to increase the classification performance. We measure the performance of our models in an extensive cross-validati...
| Publicado en: | Journal of Biomedicine & Biotechnology pp. 7p - 8 |
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| Autores principales: | , , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
2008 Regular issue
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=105557259&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 105557259 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 11107243 137K jtl: Journal of Biomedicine & Biotechnology issn: 11107243 maglogo: N pubinfo: dt: 2008 Regular issue pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 105557259 105557259 2010050616 10.1155/2008/218097 NLM18464915 105557259 ppf: 7p ppct: 1 formats: fmt: @attributes: type: P tig: atl: Classification models for early detection of prostate cancer. aug: au: Wichard JD Cammann H Stephan C Tolxdorff T affil: Institute of Medical Informatics, Charité - Universitätsmedizin, Hindenburgdamm 30, 12200 Berlin, Germany; joergwichard@web.de sug: subj: Decision Support Systems, Clinical Diagnosis, Computer Assisted Methods Models, Biological Prostatic Neoplasms Classification Prostatic Neoplasms Diagnosis Data Analysis Software Discriminant Analysis Logistic Regression Male Models, Statistical Predictive Value of Tests Reproducibility of Results ROC Curve Sensitivity and Specificity Human Male ab: We investigate the performance of different classification models and their ability to recognize prostate cancer in an early stage. We build ensembles of classification models in order to increase the classification performance. We measure the performance of our models in an extensive cross-validation procedure and compare different classification models. The datasets come from clinical examinations and some of the classification models are already in use to support the urologists in their clinical work. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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