Prediction of Pathological Stage of Prostate Cancer by Neuro Fuzzy System

Pubblicato da il Mar 18, 2013 in | Commenti disabilitati su Prediction of Pathological Stage of Prostate Cancer by Neuro Fuzzy System

==inizio abstract==

Since the advent of the preoperative staging table/nomogram, the clinical staging of localized or locally advanced prostate cancer has been revolutionized both for radical surgery and radiotherapy. These predictive scales are used for the calculation of possible oncological outcomes or probability of extraprostatic extension in the pathological stage, for example, seminal vesicle involvement (SVI), by combining clinical parameters/variables such as serum variable prostate-specific antigen levels, digital rectal examination findings, Gleason score at prostate biopsy, and percentage of positive biopsy cores (%positive cores). Although extraprostatic disease does not necessarily indicate incurable disease, SVI has been associated with poor oncological outcomes. The prediction of these pathological outcomes prior to surgery is significant in clinical practice, but there has been no study examining which clinical parameters reflect each of SVI, PSM, and PNI; such analyses may confirm the feasibility of staging nomograms also based on pathological approaches.
The aim of this work is to investigate the performance of some soft computing systems in the classification of patients with confined or non-confined cancer.

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==fine abstract==