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dc.contributor.authorKenawy, Aen_US
dc.contributor.authorKhanji, Men_US
dc.contributor.authorChirvasa, Men_US
dc.contributor.authorFung, Ken_US
dc.contributor.authorSojoudi, Aen_US
dc.contributor.authorPaiva, JMen_US
dc.contributor.authorSamy, Nen_US
dc.contributor.authorFarid, Wen_US
dc.contributor.authorKhalil, Ten_US
dc.contributor.authorPetersen, Sen_US
dc.date.accessioned2022-05-06T10:50:44Z
dc.date.issued2021-02-08en_US
dc.identifier.issn2047-2404en_US
dc.identifier.urihttps://qmro.qmul.ac.uk/xmlui/handle/123456789/78240
dc.publisherOxford University Press (OUP)en_US
dc.relation.ispartofEuropean Heart Journal - Cardiovascular Imagingen_US
dc.subjectBiomedical Imagingen_US
dc.subjectHeart Diseaseen_US
dc.subjectCardiovascularen_US
dc.subject3 Good Health and Well Beingen_US
dc.titleApplication of a machine learning contouring tool for the evaluation of left ventricular strain in clinical practiceen_US
dc.typeArticle
dc.identifier.doi10.1093/ehjci/jeaa356.259en_US
pubs.issueSupplement_1en_US
pubs.notesNot knownen_US
pubs.volume22en_US


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