Machine learning algorithms’ accuracy in predicting kidney disease progression: a systematic review and meta-analysis

BACKGROUND: Kidney disease progression rates vary among patients. Rapid and accurate prediction of kidney disease outcomes is crucial for disease management. In recent years, various prediction models using Machine Learning (ML) algorithms have been established in nephrology. However, their accuracy...

Descripción completa

Detalles Bibliográficos
Autores principales: Lei, Nuo, Zhang, Xianlong, Wei, Mengting, Lao, Beini, Xu, Xueyi, Zhang, Min, Chen, Huifen, Xu, Yanmin, Xia, Bingqing, Zhang, Dingjun, Dong, Chendi, Fu, Lizhe, Tang, Fang, Wu, Yifan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9341041/
https://www.ncbi.nlm.nih.gov/pubmed/35915457
http://dx.doi.org/10.1186/s12911-022-01951-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9341041/
https://www.ncbi.nlm.nih.gov/pubmed/35915457
http://dx.doi.org/10.1186/s12911-022-01951-1

Ejemplares similares