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Random forest-based modelling to detect biomarkers for prostate cancer progression
BACKGROUND: The clinical course of prostate cancer (PCa) is highly variable, demanding an individualized approach to therapy. Overtreatment of indolent PCa cases, which likely do not progress to aggressive stages, may be associated with severe side effects and considerable costs. These could be avoi...
Autores principales: | Toth, Reka, Schiffmann, Heiko, Hube-Magg, Claudia, Büscheck, Franziska, Höflmayer, Doris, Weidemann, Sören, Lebok, Patrick, Fraune, Christoph, Minner, Sarah, Schlomm, Thorsten, Sauter, Guido, Plass, Christoph, Assenov, Yassen, Simon, Ronald, Meiners, Jan, Gerhäuser, Clarissa |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6805338/ https://www.ncbi.nlm.nih.gov/pubmed/31640781 http://dx.doi.org/10.1186/s13148-019-0736-8 |
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