Development of Interpretable Predictive Models for BPH and Prostate Cancer | Zendy

Pablo Bermejo | Zendy; Alicia Vivo | Zendy; Pedro Juan Tárraga | Zendy; José Antonio RodríguezMontes | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Development of Interpretable Predictive Models for BPH and Prostate Cancer

Author(s) -

Pablo Bermejo,

Alicia Vivo,

Pedro Juan Tárraga,

José Antonio RodríguezMontes

Publication year - 2015

Publication title -

clinical medicine insights oncology

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.601

H-Index - 26

ISSN - 1179-5549

DOI - 10.4137/cmo.s19739

Subject(s) - prostate cancer , medicine , prostate , logistic regression , rectal examination , predictive value , urology , prostate biopsy , hyperplasia , prostate specific antigen , receiver operating characteristic , oncology , cancer

Traditional methods for deciding whether to recommend a patient for a prostate biopsy are based on cut-off levels of stand-alone markers such as prostate-specific antigen (PSA) or any of its derivatives. However, in the last decade we have seen the increasing use of predictive models that combine, in a non-linear manner, several predictives that are better able to predict prostate cancer (PC), but these fail to help the clinician to distinguish between PC and benign prostate hyperplasia (BPH) patients. We construct two new models that are capable of predicting both PC and BPH.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research