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A risk prediction model of gene signatures in ovarian cancer through bagging of GA-XGBoost models
INTRODUCTION: Ovarian cancer (OC) is one of the most frequent gynecologic cancers among women, and high-accuracy risk prediction techniques are essential to effectively select the best intervention strategies and clinical management for OC patients at different risk levels. Current risk prediction m...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8132202/ https://www.ncbi.nlm.nih.gov/pubmed/34026291 http://dx.doi.org/10.1016/j.jare.2020.11.006 |