Identification of AKI signatures and classification patterns in ccRCC based on machine learning

BACKGROUND: Acute kidney injury can be mitigated if detected early. There are limited biomarkers for predicting acute kidney injury (AKI). In this study, we used public databases with machine learning algorithms to identify novel biomarkers to predict AKI. In addition, the interaction between AKI an...

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Detalles Bibliográficos
Autores principales: Wang, Li, Peng, Fei, Li, Zhen Hua, Deng, Yu Fei, Ruan, Meng Na, Mao, Zhi Guo, Li, Lin
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/PMC10244623/
https://www.ncbi.nlm.nih.gov/pubmed/37293297
http://dx.doi.org/10.3389/fmed.2023.1195678

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10244623/
https://www.ncbi.nlm.nih.gov/pubmed/37293297
http://dx.doi.org/10.3389/fmed.2023.1195678

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