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Integrating Somatic Mutations for Breast Cancer Survival Prediction Using Machine Learning Methods

Breast cancer is the most common malignancy in women, and because it has a high mortality rate, it is urgent to develop computational methods to increase the accuracy of breast cancer survival predictive models. Although multi-omics data such as gene expression have been extensively used in recent s...

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Bibliographische Detailangaben
Veröffentlicht in:Front Genet
Hauptverfasser: He, Zongzhen, Zhang, Junying, Yuan, Xiguo, Zhang, Yuanyuan
Format: Artigo
Sprache:Inglês
Veröffentlicht: Frontiers Media S.A. 2021
Schlagworte:
Online Zugang:https://ncbi.nlm.nih.gov/pmc/articles/PMC7848170/
https://ncbi.nlm.nih.gov/pubmed/33537063
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fgene.2020.632901
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