An Explainable Machine Learning Approach Reveals Prognostic Significance of Right Ventricular Dysfunction in Nonischemic Cardiomyopathy
Fahmy A, Csecs I, Arafati A, Assana S, Yankama T, Al-Otaibi T, Rodriguez J, Chen Y, Ngo L, Manning W, Kwong R, Nezafat R. An Explainable Machine Learning Approach Reveals Prognostic Significance of Right Ventricular Dysfunction in Nonischemic Cardiomyopathy. JACC Cardiovascular Imaging 2022, 15: 766-779. PMID: 35033500, DOI: 10.1016/j.jcmg.2021.11.029.Peer-Reviewed Original ResearchMeSH KeywordsCardiomyopathiesFemaleHumansMachine LearningPredictive Value of TestsPrognosisVentricular Dysfunction, RightConceptsNonischemic dilated cardiomyopathyBeth Israel Deaconess Medical CenterComposite endpointRight ventricular (RV) dysfunctionCardiovascular hospitalizationRisk prediction modelAdverse outcomesRisk markersMarker of adverse outcomeCardiac magnetic resonance markersRisk stratification of patientsRight ventricular dysfunctionRV ejection fractionMedical CenterFollow-up durationCardiac magnetic resonanceEnd-diastolic volumeStratification of patientsArea under the curveAll-cause deathHigh-risk thresholdVentricular dysfunctionEjection fractionNonischemic cardiomyopathyPrognostic significance