Publication:

Development and evaluation of uncertainty quantifying machine learning models to predict piperacillin plasma concentrations in critically ill patients

Date

2022
Journal article
https://doi.org/10.1186/s12911-022-01970-y
Simple item page Full metadata Statistics
 
dc.contributor.authorVerhaeghe, Jarne
dc.contributor.authorDhaese, Sofie A. M.
dc.contributor.authorDe Corte, Thomas
dc.contributor.authorVander Mijnsbrugge, David
dc.contributor.authorAardema, Heleen
dc.contributor.authorZijlstra, Jan G.
dc.contributor.authorVerstraete, Alain G.
dc.contributor.authorStove, Veronique
dc.contributor.authorColin, Pieter
dc.contributor.authorOngenae, Femke
dc.contributor.authorDe Waele, Jan J.
dc.contributor.authorVan Hoecke, Sofie
dc.contributor.imecauthorVerhaeghe, Jarne
dc.contributor.imecauthorVander Mijnsbrugge, David
dc.contributor.imecauthorOngenae, Femke
dc.contributor.imecauthorVan Hoecke, Sofie
dc.contributor.orcidimecVerhaeghe, Jarne::0000-0002-3322-150X
dc.contributor.orcidimecVander Mijnsbrugge, David::0000-0002-9918-3438
dc.contributor.orcidimecOngenae, Femke::0000-0003-2529-5477
dc.contributor.orcidimecVan Hoecke, Sofie::0000-0002-7865-6793
dc.date.accessioned2023-03-23T15:12:40Z
dc.date.available2022-09-05T02:37:54Z
dc.date.available2022-09-05T13:07:54Z
dc.date.available2023-03-23T15:12:40Z
dc.date.embargo2022-08-25
dc.date.issued2022
dc.description.wosFundingTextPart of the research was funded by the FWO Junior Research project HEROI2C that investigates hybrid machine learning for improved infection management in critically ill patients (Ref: 1881020N). Sofie A.M. Dhaese is funded by a Centre of Research Excellence Grant (APP1099452) from the Australian National Health and Medical Research Council awarded to Jason A. Roberts. Jan J. De Waele is senior clinical investigator funded by the Research Foundation Flanders (FWO, Ref. 1881020N).
dc.identifier.doi10.1186/s12911-022-01970-y
dc.identifier.issn1472-6947
dc.identifier.pmidMEDLINE:36008808
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/40347
dc.publisherBMC
dc.source.beginpageArt. 224
dc.source.endpagena
dc.source.issuena
dc.source.journalBMC MEDICAL INFORMATICS AND DECISION MAKING
dc.source.numberofpages17
dc.source.volume22
dc.subject.keywordsBETA-LACTAM ANTIBIOTICS
dc.subject.keywordsCARE
dc.subject.keywordsEQUATION
dc.subject.keywordsSEPSIS
dc.title

Development and evaluation of uncertainty quantifying machine learning models to predict piperacillin plasma concentrations in critically ill patients

dc.typeJournal article
dspace.entity.typePublication
Files

Original bundle

Name:
8146.pdf
Size:
1.8 MB
Format:
Unknown data format
Description:
Published version
Download
Publication available in collections:
Articles