2025
Complete AI-Enabled Echocardiography Interpretation With Multitask Deep Learning
Holste G, Oikonomou E, Tokodi M, Kovács A, Wang Z, Khera R. Complete AI-Enabled Echocardiography Interpretation With Multitask Deep Learning. JAMA 2025, 334: 306-318. PMID: 40549400, PMCID: PMC12186137, DOI: 10.1001/jama.2025.8731.Peer-Reviewed Original ResearchMultitask deep learningAI systemsDiagnostic classification tasksClassification taskDeep learningArtificial intelligenceArea under the receiver operating characteristic curveYale New Haven Health SystemTransthoracic echocardiography studyTransthoracic echocardiographyVentricular systolic dysfunctionParameter estimation taskSystolic dysfunctionDiagnosis tasksEchocardiographic videosRight ventricular systolic dysfunctionLeft ventricular ejection fractionAI predictionsEstimation taskVentricular ejection fractionSevere aortic stenosisManual reportingReceiver operating characteristic curveTaskClinical workflowArtificial intelligence-enabled electrocardiography and echocardiography to track preclinical progression of transthyretin amyloid cardiomyopathy
Oikonomou E, Sangha V, Vasisht Shankar S, Coppi A, Krumholz H, Nasir K, Miller E, Gallegos Kattan C, Al-Mallah M, Al-Kindi S, Khera R. Artificial intelligence-enabled electrocardiography and echocardiography to track preclinical progression of transthyretin amyloid cardiomyopathy. European Heart Journal 2025, ehaf450. PMID: 40679604, DOI: 10.1093/eurheartj/ehaf450.Peer-Reviewed Original ResearchTransthyretin amyloid cardiomyopathyTransthoracic echocardiographyATTR-CMAmyloid cardiomyopathyPreclinical progressAI-ECGRetrospective analysisDiagnosis of transthyretin amyloid cardiomyopathyDeep learning modelsAge/sex matched controlsRetrospective analysis of individualsLearning modelsPreclinical testingElectrocardiography imagingEchocardiographyHouston Methodist HospitalYale New Haven Health SystemAdvanced imagingElectrocardiographyPreclinical coursesCardiomyopathyPreclinical stage
2023
Predicting aortic stenosis progression using a video-based deep learning model of aortic stenosis built for single-view two-dimensional echocardiography
Oikonomou E, Holste G, Mcnamara R, Velazquez E, Nadkarni G, Ouyang D, Krumholz H, Wang Z, Khera R. Predicting aortic stenosis progression using a video-based deep learning model of aortic stenosis built for single-view two-dimensional echocardiography. European Heart Journal 2023, 44: ehad655.040. DOI: 10.1093/eurheartj/ehad655.040.Peer-Reviewed Original ResearchLeft ventricular ejection fractionSevere aortic stenosisAortic stenosisAS progressionAV VmaxTransthoracic echocardiographyYale New Haven Health SystemBaseline left ventricular ejection fractionAortic stenosis progressionModerate aortic stenosisRetrospective cohort studyVentricular ejection fractionTwo-dimensional echocardiographyMean rateModerate ASAS severityCohort studyEjection fractionPatient sexStenosis progressionTTE studiesEligible participantsSerial monitoringSpecialized centersTimely diagnosis
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