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A machine learning-derived risk score to predict left ventricular diastolic dysfunction from clinical cardiovascular magnetic resonance imaging

IntroductionThe evaluation of left ventricular diastolic dysfunction (LVDD) by clinical cardiac magnetic resonance (CMR) remains a challenge. We aimed to train and evaluate a machine-learning (ML) algorithm for the assessment of LVDD by clinical CMR variables and to investigate its prognostic value...

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Principais autores: Qingtao Zhou, Lin Wang, Jason Craft, Jonathan Weber, Michael Passick, Nora Ngai, Omar K. Khalique, James W. Goldfarb, Eddy Barasch, J. Jane Cao
פורמט: Artigo
שפה:Inglês
יצא לאור: Frontiers Media S.A. 2024-06-01
סדרה:Frontiers in Cardiovascular Medicine
נושאים:
machine learning
LVDD
heart failure
echocardiography
cardiac magnetic resonance imaging
גישה מקוונת:https://www.frontiersin.org/articles/10.3389/fcvm.2024.1382418/full
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