Prostate cancer prediction using the random forest algorithm that takes into account transrectal ultrasound findings, age, and serum levels of prostate-specific antigen

Prostate cancer prediction using the random forest algorithm that takes into account transrectal ultrasound findings, age, and serum levels of prostate-specific antigen

The aim of this study is to evaluate the ability of the random forest algorithm that combines data on transrectal ultrasound findings, age, and serum levels of prostate-specific antigen to predict prostate carcinoma. Clinico-demographic data were analyzed for 941 patients with prostate diseases trea...

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Bibliographic Details
Main Authors: Li-Hong Xiao, Pei-Ran Chen, Zhong-Ping Gou, Yong-Zhong Li, Mei Li, Liang-Cheng Xiang, Ping Feng
Format: Article
Language:English
Published: Wolters Kluwer Medknow Publications 2017-01-01
Series:Asian Journal of Andrology
Subjects:
diagnosis; prostate cancer; prostate-specific antigen; random forest algorithm; transrectal ultrasound characteristics
Online Access:http://www.ajandrology.com/article.asp?issn=1008-682X;year=2017;volume=19;issue=5;spage=586;epage=590;aulast=Xiao

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http://www.ajandrology.com/article.asp?issn=1008-682X;year=2017;volume=19;issue=5;spage=586;epage=590;aulast=Xiao

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