Optimized Identification of Advanced Chronic Kidney Disease and Absence of Kidney Disease by Combining Different Electronic Health Data Resources and by Applying Machine Learning Strategies

Automated identification of advanced chronic kidney disease (CKD ≥ III) and of no known kidney disease (NKD) can support both clinicians and researchers. We hypothesized that identification of CKD and NKD can be improved, by combining information from different electronic health record (EHR) resourc...

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Detalles Bibliográficos
Autores principales: Weber, Christoph, Röschke, Lena, Modersohn, Luise, Lohr, Christina, Kolditz, Tobias, Hahn, Udo, Ammon, Danny, Betz, Boris, Kiehntopf, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7563476/
https://www.ncbi.nlm.nih.gov/pubmed/32932685
http://dx.doi.org/10.3390/jcm9092955

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7563476/
https://www.ncbi.nlm.nih.gov/pubmed/32932685
http://dx.doi.org/10.3390/jcm9092955

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