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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.

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Title: 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.
Authors: Weber C; Department of Clinical Chemistry and Laboratory Diagnostics and Integrated Biobank Jena (IBBJ), Jena University Hospital, 07747 Jena, Germany., Röschke L; Department of Clinical Chemistry and Laboratory Diagnostics and Integrated Biobank Jena (IBBJ), Jena University Hospital, 07747 Jena, Germany., Modersohn L; Jena University Language & Information Engineering (JULIE) Lab, Friedrich Schiller University Jena, 07743 Jena, Germany., Lohr C; Jena University Language & Information Engineering (JULIE) Lab, Friedrich Schiller University Jena, 07743 Jena, Germany., Kolditz T; Jena University Language & Information Engineering (JULIE) Lab, Friedrich Schiller University Jena, 07743 Jena, Germany., Hahn U; Jena University Language & Information Engineering (JULIE) Lab, Friedrich Schiller University Jena, 07743 Jena, Germany., Ammon D; Data Integration Center, Jena University Hospital, 07743 Jena, Germany., Betz B; Department of Clinical Chemistry and Laboratory Diagnostics and Integrated Biobank Jena (IBBJ), Jena University Hospital, 07747 Jena, Germany., Kiehntopf M; Department of Clinical Chemistry and Laboratory Diagnostics and Integrated Biobank Jena (IBBJ), Jena University Hospital, 07747 Jena, Germany.
Source: Journal of clinical medicine [J Clin Med] 2020 Sep 12; Vol. 9 (9). Date of Electronic Publication: 2020 Sep 12.
Publication Type: Journal Article
Journal Info: Publisher: MDPI AG Country of Publication: Switzerland NLM ID: 101606588 Publication Model: Electronic Cited Medium: Print ISSN: 2077-0383 (Print) Linking ISSN: 20770383 NLM ISO Abbreviation: J Clin Med Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2077-0383
DOI:10.3390/jcm9092955