Publication:

Comparison between the EKFC-equation and machine learning models to predict Glomerular Filtration Rate

Date

2024
Journal article
https://doi.org/10.1038/s41598-024-77618-w
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dc.contributor.authorNakano, Felipe Kenji
dc.contributor.authorAkesson, Anna
dc.contributor.authorde Boer, Jasper
dc.contributor.authorDedja, Klest
dc.contributor.authorD'hondt, Robbe
dc.contributor.authorFatemi, Naghmeh
dc.contributor.authorBjork, Jonas
dc.contributor.authorCourbebaisse, Marie
dc.contributor.authorCouzi, Lionel
dc.contributor.authorEbert, Natalie
dc.contributor.authorEriksen, Bjorn O.
dc.contributor.authorDalton, R. Neil
dc.contributor.authorDerain-Dubourg, Laurence
dc.contributor.authorGaillard, Francois
dc.contributor.authorGarrouste, Cyril
dc.contributor.authorGrubb, Anders
dc.contributor.authorJacquemont, Lola
dc.contributor.authorHansson, Magnus
dc.contributor.authorKamar, Nassim
dc.contributor.authorLegendre, Christophe
dc.contributor.imecauthorNakano, Felipe Kenji
dc.contributor.imecauthorde Boer, Jasper
dc.contributor.imecauthorDedja, Klest
dc.contributor.imecauthorD'hondt, Robbe
dc.contributor.imecauthorFatemi, Naghmeh
dc.contributor.imecauthorVens, Celine
dc.contributor.orcidimecNakano, Felipe Kenji::0000-0002-4884-9420
dc.contributor.orcidimecde Boer, Jasper::0000-0002-1093-7409
dc.contributor.orcidimecDedja, Klest::0000-0001-5280-6717
dc.contributor.orcidimecD'hondt, Robbe::0000-0001-7843-2178
dc.contributor.orcidimecFatemi, Naghmeh::0000-0002-7809-9747
dc.contributor.orcidimecVens, Celine::0000-0003-0983-256X
dc.date.accessioned2025-01-15T09:53:15Z
dc.date.available2024-11-12T16:39:49Z
dc.date.available2025-01-15T09:53:15Z
dc.date.embargo2024-11-02
dc.date.issued2024
dc.description.wosFundingTextThe Chronic Renal Insufficiency Cohort Study (CRIC) was conducted by the CRIC Investigators and supported by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). The data from the CRIC Study reported here were supplied by the NIDDK Central Repositories. This manuscript was not prepared in collaboration with investigators of the CRIC study and does not necessarily reflect the opinions or views of the CRIC study, the NIDDK Central Repositories, or the NIDDK.
dc.identifier.doi10.1038/s41598-024-77618-w
dc.identifier.issn2045-2322
dc.identifier.pmidMEDLINE:39487227
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/44771
dc.publisherNATURE PORTFOLIO
dc.source.beginpageArt. 26383
dc.source.endpageN/A
dc.source.issue1
dc.source.journalSCIENTIFIC REPORTS
dc.source.numberofpages9
dc.source.volume14
dc.title

Comparison between the EKFC-equation and machine learning models to predict Glomerular Filtration Rate

dc.typeJournal article
dspace.entity.typePublication
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