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Clinically Distinct Subtypes of Acute Kidney Injury on Hospital Admission Identified by Machine Learning Consensus Clustering
Background: We aimed to cluster patients with acute kidney injury at hospital admission into clinically distinct subtypes using an unsupervised machine learning approach and assess the mortality risk among the distinct clusters. Methods: We performed consensus clustering analysis based on demographi...
Autores principales: | Thongprayoon, Charat, Vaitla, Pradeep, Nissaisorakarn, Voravech, Mao, Michael A., Genovez, Jose L. Zabala, Kattah, Andrea G., Pattharanitima, Pattharawin, Vallabhajosyula, Saraschandra, Keddis, Mira T., Qureshi, Fawad, Dillon, John J., Garovic, Vesna D., Kashani, Kianoush B., Cheungpasitporn, Wisit |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8544570/ https://www.ncbi.nlm.nih.gov/pubmed/34698185 http://dx.doi.org/10.3390/medsci9040060 |
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