Publication:
Temporal shift and predictive performance of machine learning for heart transplant outcomes
| dc.contributor.author | Miller, Robert J. H. | |
| dc.contributor.author | Sabovcik, Frantisek | |
| dc.contributor.author | Cauwenberghs, Nicholas | |
| dc.contributor.author | Vens, Celine | |
| dc.contributor.author | Khush, Kiran K. | |
| dc.contributor.author | Heidenreich, Paul A. | |
| dc.contributor.author | Haddad, Francois | |
| dc.contributor.author | Kuznetsova, Tatiana | |
| dc.contributor.imecauthor | Vens, Celine | |
| dc.contributor.orcidimec | Vens, Celine::0000-0003-0983-256X | |
| dc.date.accessioned | 2022-12-01T15:40:59Z | |
| dc.date.available | 2022-10-19T02:49:25Z | |
| dc.date.available | 2022-12-01T15:40:59Z | |
| dc.date.issued | 2022 | |
| dc.description.wosFundingText | This 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. | |
| dc.identifier.doi | 10.1016/j.healun.2022.03.019 | |
| dc.identifier.issn | 1053-2498 | |
| dc.identifier.pmid | MEDLINE:35568604 | |
| dc.identifier.uri | https://imec-publications.be/handle/20.500.12860/40591 | |
| dc.publisher | ELSEVIER SCIENCE INC | |
| dc.source.beginpage | 928 | |
| dc.source.endpage | 936 | |
| dc.source.issue | 7 | |
| dc.source.journal | JOURNAL OF HEART AND LUNG TRANSPLANTATION | |
| dc.source.numberofpages | 9 | |
| dc.source.volume | 41 | |
| dc.subject.keywords | CARDIAC TRANSPLANTATION | |
| dc.subject.keywords | UNITED NETWORK | |
| dc.subject.keywords | DONOR AGE | |
| dc.subject.keywords | SURVIVAL | |
| dc.subject.keywords | MORTALITY | |
| dc.subject.keywords | RISK | |
| dc.subject.keywords | REGISTRY | |
| dc.subject.keywords | SYSTEM | |
| dc.subject.keywords | IMPACT | |
| dc.title | Temporal shift and predictive performance of machine learning for heart transplant outcomes | |
| dc.type | Journal article | |
| dspace.entity.type | Publication | |
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