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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...
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 |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
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 |
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