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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Detalles Bibliográficos
Autores principales: Xiao, Li-Hong, Chen, Pei-Ran, Gou, Zhong-Ping, Li, Yong-Zhong, Li, Mei, Xiang, Liang-Cheng, Feng, Ping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2017
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5566854/
https://www.ncbi.nlm.nih.gov/pubmed/27586028
http://dx.doi.org/10.4103/1008-682X.186884

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5566854/
https://www.ncbi.nlm.nih.gov/pubmed/27586028
http://dx.doi.org/10.4103/1008-682X.186884

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