Prediction of survival outcomes in patients with epithelial ovarian cancer using machine learning methods

OBJECTIVES: The aim of this study was to develop a new prognostic classification for epithelial ovarian cancer (EOC) patients using gradient boosting (GB) and to compare the accuracy of the prognostic model with the conventional statistical method. METHODS: Information of EOC patients from Samsung M...

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Detalles Bibliográficos
Autores principales: Paik, E Sun, Lee, Jeong-Won, Park, Jeong-Yeol, Kim, Ju-Hyun, Kim, Mijung, Kim, Tae-Joong, Choi, Chel Hun, Kim, Byoung-Gie, Bae, Duk-Soo, Seo, Sung Wook
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Asian Society of Gynecologic Oncology; Korean Society of Gynecologic Oncology 2019
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6543110/
https://www.ncbi.nlm.nih.gov/pubmed/31074247
http://dx.doi.org/10.3802/jgo.2019.30.e65

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6543110/
https://www.ncbi.nlm.nih.gov/pubmed/31074247
http://dx.doi.org/10.3802/jgo.2019.30.e65

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