Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/44671
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dc.contributor.authorWOUTERS, Femke-
dc.contributor.authorGRUWEZ, Henri-
dc.contributor.authorBARTHELS, Myrte-
dc.contributor.authorMESOTTEN, Dieter-
dc.contributor.authorVerhaert, David-
dc.contributor.authorPISON, Laurent-
dc.contributor.authorErnon, Ludovic-
dc.contributor.authorHAEMERS, Phoebe-
dc.contributor.authorNUYENS, Dieter-
dc.contributor.authorDHONT, Sebastiaan-
dc.contributor.authorSMEETS, Christophe-
dc.contributor.authorVRANKEN, Julie-
dc.contributor.authorVANDERVOORT, Pieter-
dc.date.accessioned2024-11-19T07:02:23Z-
dc.date.available2024-11-19T07:02:23Z-
dc.date.issued2024-
dc.date.submitted2024-11-08T13:11:15Z-
dc.identifier.citationJournal of the American College of Cardiology, 83 (13) , p. 2447-
dc.identifier.urihttp://hdl.handle.net/1942/44671-
dc.description.abstractBackground: Artificial intelligence (AI)-enabled ECG algorithms can predict underlying paroxysmal AF from ECGs recorded during sinus rhythm within a 30-day window. Their predictive value in cryptogenic stroke patients over a 1-year duration is unknown.-
dc.language.isoen-
dc.publisherELSEVIER SCIENCE INC-
dc.titlePredicting paroxysmal atrial fibrallation in cryptogenic stroke patients from an electrocardiogram in sinus rhythm using artificial intelligence-
dc.typeJournal Contribution-
local.bibliographicCitation.conferencedateAPR 06-08, 2024-
local.bibliographicCitation.conferencename73rd Annual Scientific Session & Expo of the-
local.bibliographicCitation.conferencenameAmerican-College-of-Cardiology (ACC)-
local.bibliographicCitation.conferenceplaceAtlanta, GEORGIA-
dc.identifier.issue13-
dc.identifier.spage2447-
dc.identifier.volume83-
local.format.pages1-
local.bibliographicCitation.jcatM-
local.publisher.placeSTE 800, 230 PARK AVE, NEW YORK, NY 10169 USA-
local.type.refereedRefereed-
local.type.specifiedMeeting Abstract-
dc.identifier.isi001324901502481-
local.provider.typewosris-
local.description.affiliationHasselt Univ, Hasselt, Belgium.-
local.description.affiliationZiekenhuis Oost Limburg, Genk, Belgium.-
local.uhasselt.internationalno-
item.fulltextWith Fulltext-
item.accessRightsOpen Access-
item.fullcitationWOUTERS, Femke; GRUWEZ, Henri; BARTHELS, Myrte; MESOTTEN, Dieter; Verhaert, David; PISON, Laurent; Ernon, Ludovic; HAEMERS, Phoebe; NUYENS, Dieter; DHONT, Sebastiaan; SMEETS, Christophe; VRANKEN, Julie & VANDERVOORT, Pieter (2024) Predicting paroxysmal atrial fibrallation in cryptogenic stroke patients from an electrocardiogram in sinus rhythm using artificial intelligence. In: Journal of the American College of Cardiology, 83 (13) , p. 2447.-
item.contributorWOUTERS, Femke-
item.contributorGRUWEZ, Henri-
item.contributorBARTHELS, Myrte-
item.contributorMESOTTEN, Dieter-
item.contributorVerhaert, David-
item.contributorPISON, Laurent-
item.contributorErnon, Ludovic-
item.contributorHAEMERS, Phoebe-
item.contributorNUYENS, Dieter-
item.contributorDHONT, Sebastiaan-
item.contributorSMEETS, Christophe-
item.contributorVRANKEN, Julie-
item.contributorVANDERVOORT, Pieter-
crisitem.journal.issn0735-1097-
crisitem.journal.eissn1558-3597-
Appears in Collections:Research publications
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