A random forest classifier predicts recurrence risk in patients with ovarian cancer

Ovarian cancer (OC) is associated with a poor prognosis due to difficulties in early detection. The aims of the present study were to construct a recurrence risk prediction model and to reveal important OC genes or pathways. RNA sequencing data was obtained for 307 OC samples, and the corresponding...

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Detalles Bibliográficos
Autores principales: Cheng, Li, Li, Lin, Wang, Liling, Li, Xiaofang, Xing, Hui, Zhou, Jinting
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2018
Materias:
Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6102638/
https://www.ncbi.nlm.nih.gov/pubmed/30066910
http://dx.doi.org/10.3892/mmr.2018.9300

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6102638/
https://www.ncbi.nlm.nih.gov/pubmed/30066910
http://dx.doi.org/10.3892/mmr.2018.9300

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