Literature DB >> 11790275

Predictive modeling techniques in prostate cancer.

A Tewari1, C Porter, J Peabody, E D Crawford, R Demers, C C Johnson, J T Wei, G W Divine, C O'Donnell, E J Gamito, M Menon.   

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.

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Year:  2001        PMID: 11790275     DOI: 10.1089/10915360152745812

Source DB:  PubMed          Journal:  Mol Urol        ISSN: 1091-5362


  2 in total

1.  Prediction of Pathological Stage in Patients with Prostate Cancer: A Neuro-Fuzzy Model.

Authors:  Georgina Cosma; Giovanni Acampora; David Brown; Robert C Rees; Masood Khan; A Graham Pockley
Journal:  PLoS One       Date:  2016-06-03       Impact factor: 3.240

2.  A Deep Belief Network and Dempster-Shafer-Based Multiclassifier for the Pathology Stage of Prostate Cancer.

Authors:  Jae Kwon Kim; Mun Joo Choi; Jong Sik Lee; Jun Hyuk Hong; Choung-Soo Kim; Seong Il Seo; Chang Wook Jeong; Seok-Soo Byun; Kyo Chul Koo; Byung Ha Chung; Yong Hyun Park; Ji Youl Lee; In Young Choi
Journal:  J Healthc Eng       Date:  2018-03-19       Impact factor: 2.682

  2 in total

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