Ashutosh Tewari, Christopher Porter, J. Peabody, E. David Crawford, Raymond Demers, Christine C. Johnson, John T. Wei, George W. Divine, Colin O'Donnell, E. Gamito, Mani Menon
{"title":"Predictive modeling techniques in prostate cancer.","authors":"Ashutosh Tewari, Christopher Porter, J. Peabody, E. David Crawford, Raymond Demers, Christine C. Johnson, John T. Wei, George W. Divine, Colin O'Donnell, E. Gamito, Mani Menon","doi":"10.1089/10915360152745812","DOIUrl":null,"url":null,"abstract":"A number of new predictive modeling techniques have emerged in the past several years. These methods can be used independently or in combination with traditional modeling techniques to produce useful tools for the management of prostate cancer. Investigators should be aware of these techniques and avail themselves of their potentially useful properties. This review outlines selected predictive methods that can be used to develop models that may be useful to patients and clinicians for prostate cancer management.","PeriodicalId":80296,"journal":{"name":"Molecular urology","volume":"5 4 1","pages":"147-52"},"PeriodicalIF":0.0000,"publicationDate":"2001-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1089/10915360152745812","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Molecular urology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1089/10915360152745812","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
A number of new predictive modeling techniques have emerged in the past several years. These methods can be used independently or in combination with traditional modeling techniques to produce useful tools for the management of prostate cancer. Investigators should be aware of these techniques and avail themselves of their potentially useful properties. This review outlines selected predictive methods that can be used to develop models that may be useful to patients and clinicians for prostate cancer management.