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dc.contributor.authorMiller, Robert J. H.
dc.contributor.authorSabovcik, Frantisek
dc.contributor.authorCauwenberghs, Nicholas
dc.contributor.authorVens, Celine
dc.contributor.authorKhush, Kiran K.
dc.contributor.authorHeidenreich, Paul A.
dc.contributor.authorHaddad, Francois
dc.contributor.authorKuznetsova, Tatiana
dc.date.accessioned2022-12-01T15:40:59Z
dc.date.available2022-10-19T02:49:25Z
dc.date.available2022-12-01T15:40:59Z
dc.date.issued2022
dc.identifier.issn1053-2498
dc.identifier.otherWOS:000861338000015
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/40591.2
dc.sourceWOS
dc.titleTemporal shift and predictive performance of machine learning for heart transplant outcomes
dc.typeJournal article
dc.contributor.imecauthorVens, Celine
dc.contributor.orcidimecVens, Celine::0000-0003-0983-256X
dc.identifier.doi10.1016/j.healun.2022.03.019
dc.source.numberofpages9
dc.source.peerreviewyes
dc.source.beginpage928
dc.source.endpage936
dc.source.journalJOURNAL OF HEART AND LUNG TRANSPLANTATION
dc.identifier.pmidMEDLINE:35568604
dc.source.issue7
dc.source.volume41
imec.availabilityPublished - imec
dc.description.wosFundingTextThis work was supported in part by Health Resources and Services Administration contract 234-2005-370011C. The content is the responsibility of the authors alone and does not necessarily reflect the views or policies of the Department of Health and Human Services, nor does mention of trade names, commercial products, or organizations imply endorsement by the U.S. Government. Research Unit Hypertension and Cardiovascular Epidemiology, University of Leuven, Belgium is supported by the Research Foundation Flanders (grant numbers 1225021N, 1S07421N and G0C5319N). We also acknowledge the support of Stanford Cardiovascular Institute and Stanford Cardiac Surgery Department.


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