Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/44490
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dc.contributor.authorMoroni, A.-
dc.contributor.authorMascaretti, A.-
dc.contributor.authorDENS, Jo-
dc.contributor.authorKnaapen, P.-
dc.contributor.authorBennett, J.-
dc.contributor.authorUngureanu, C.-
dc.contributor.authorKayaert, P.-
dc.contributor.authorCoussement, P.-
dc.contributor.authorSonck, J.-
dc.contributor.authorVescovo, G.-
dc.contributor.authorAgostoni, P.-
dc.contributor.authorZivelonghi, C.-
dc.date.accessioned2024-10-17T11:50:39Z-
dc.date.available2024-10-17T11:50:39Z-
dc.date.issued2024-
dc.date.submitted2024-10-15T14:31:42Z-
dc.identifier.citationJACC: Cardiovascular Interventions, 17 (4) , p. S14-
dc.identifier.urihttp://hdl.handle.net/1942/44490-
dc.language.isoen-
dc.publisherELSEVIER SCIENCE INC-
dc.titleMachine Learning- Based Algorithm to Predict Procedural Success in a Large European Cohort of Hybrid Chronic Total Occlusion - Percutaneous Coronary Interventions-
dc.typeJournal Contribution-
dc.identifier.issue4-
dc.identifier.spageS14-
dc.identifier.volume17-
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-
local.bibliographicCitation.artnr100.53-
dc.identifier.isiWOS:001301849200034-
local.provider.typewosris-
local.description.affiliation[Moroni, A.; Agostoni, P.; Zivelonghi, C.] HartCtr ZNA Middelheim, Antwerp, Belgium.-
local.description.affiliation[Mascaretti, A.] Univ Padua, Padua, Italy.-
local.description.affiliation[Dens, J.] Ziekenhuis Oost Limburg, Dept Cardiol, Genk, Belgium.-
local.description.affiliation[Knaapen, P.] Univ Amsterdam, Dept Cardiol, VUMC, Med Ctr, Amsterdam, Netherlands.-
local.description.affiliation[Bennett, J.] Univ Hosp Leuven, Dept Cardiovasc Med, Leuven, Belgium.-
local.description.affiliation[Ungureanu, C.] Hop Jolimont, Dept Cardiol, Haine St Paul, Belgium.-
local.description.affiliation[Kayaert, P.] Jessa Hosp, Dept Cardiol, Hasselt, Belgium.-
local.description.affiliation[Coussement, P.] AZ Sint Jan Brugge, Dept Cardiol, Brugge, Belgium.-
local.description.affiliation[Sonck, J.] OLV Clin, Cardiovasc Ctr Aalst, Aalst, Belgium.-
local.description.affiliation[Vescovo, G.] Osped dellAngelo, Venice, Italy.-
local.uhasselt.internationalyes-
item.fulltextWith Fulltext-
item.contributorMoroni, A.-
item.contributorMascaretti, A.-
item.contributorDENS, Jo-
item.contributorKnaapen, P.-
item.contributorBennett, J.-
item.contributorUngureanu, C.-
item.contributorKayaert, P.-
item.contributorCoussement, P.-
item.contributorSonck, J.-
item.contributorVescovo, G.-
item.contributorAgostoni, P.-
item.contributorZivelonghi, C.-
item.fullcitationMoroni, A.; Mascaretti, A.; DENS, Jo; Knaapen, P.; Bennett, J.; Ungureanu, C.; Kayaert, P.; Coussement, P.; Sonck, J.; Vescovo, G.; Agostoni, P. & Zivelonghi, C. (2024) Machine Learning- Based Algorithm to Predict Procedural Success in a Large European Cohort of Hybrid Chronic Total Occlusion - Percutaneous Coronary Interventions. In: JACC: Cardiovascular Interventions, 17 (4) , p. S14.-
item.accessRightsRestricted Access-
crisitem.journal.issn1936-8798-
crisitem.journal.eissn1876-7605-
Appears in Collections:Research publications
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