A bibliometric analysis of 16,826 triple-negative breast cancer publications using multiple machine learning algorithms: Progress in the past 17 years

BACKGROUND: Triple-negative breast cancer (TNBC) is proposed at the beginning of this century, which is still the most challenging breast cancer subtype due to its aggressive behavior, including early relapse, metastatic spread, and poor survival. This study uses machine learning methods to explore...

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Detalles Bibliográficos
Autores principales: Wang, Kangtao, Zheng, Chanjuan, Xue, Lian, Deng, Dexin, Zeng, Liang, Li, Ming, Deng, Xiyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Medicine
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9945529/
https://www.ncbi.nlm.nih.gov/pubmed/36844225
http://dx.doi.org/10.3389/fmed.2023.999312

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9945529/
https://www.ncbi.nlm.nih.gov/pubmed/36844225
http://dx.doi.org/10.3389/fmed.2023.999312

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