Artificial intelligence-guided screening of under-recognized cardiomyopathies adapted for point-of-care echocardiography
Oikonomou E, Holste G, Coppi A, Mcnamara R, Nadkarni G, Krumholz H, Wang Z, Miller E, Khera R. Artificial intelligence-guided screening of under-recognized cardiomyopathies adapted for point-of-care echocardiography. European Heart Journal 2024, 45: ehae666.157. DOI: 10.1093/eurheartj/ehae666.157.Peer-Reviewed Original ResearchConvolutional neural networkMulti-labelState-of-the-art performanceState-of-the-artCustom loss functionDeep learning modelsAI frameworkNeural networkLoss functionAutomated metricsLearning modelsAugmentation approachVideoAcquisition qualityAdvanced protocolsPoint-of-care ultrasonographyImagesTransthoracic echocardiogramClassifierATTR-CMAlgorithmNetworkAI screeningAcquisitionPresence of severe ASCharacterizing the progression of subclinical cardiac amyloidosis through artificial intelligence applied to electrocardiographic images and echocardiograms
Oikonomou E, Sangha V, Coppi A, Krumholz H, Miller E, Khera R. Characterizing the progression of subclinical cardiac amyloidosis through artificial intelligence applied to electrocardiographic images and echocardiograms. European Heart Journal 2024, 45: ehae666.2089. DOI: 10.1093/eurheartj/ehae666.2089.Peer-Reviewed Original ResearchDiagnosis of ATTR-CMATTR-CMBone scintigraphy scansClinical diagnosisTransthyretin amyloid cardiomyopathyMonths of diagnosisSex-matched controlsElectrocardiographic (ECGIndolent courseCardiac amyloidosisScintigraphy scanAmyloid cardiomyopathyEchocardiographic studiesAI-ECGEchocardiogramEventual diagnosisDetect longitudinal changesConfirmatory testDiagnosisClinical diseasePercentage of individualsLongitudinal changesECGMedianMonthsArtificial intelligence applied to electrocardiographic images for scalable screening of cardiac amyloidosis
Sangha V, Oikonomou E, Krumholz H, Miller E, Khera R. Artificial intelligence applied to electrocardiographic images for scalable screening of cardiac amyloidosis. European Heart Journal 2024, 45: ehae666.3436. DOI: 10.1093/eurheartj/ehae666.3436.Peer-Reviewed Original ResearchATTR-CMBone scintigraphy scansTransthyretin amyloid cardiomyopathyPositive predictive valueAI-ECG algorithmCardiac amyloidosisScintigraphy scanAmyloid cardiomyopathyAI-ECGSex-matchedDevelopment cohortMyocardial remodelingUnder-diagnosedUnder-treatedMatched controlsPredictive valueUnder-recognizedTransthyretin stabilizersConvolutional neural networkPatientsECGArtificial intelligenceHospitalPrevalenceTransthyretinDetection of ATTR cardiac amyloidosis using a novel artificial intelligence algorithm for wearable-adapted noisy single-lead electrocardiograms
Sangha V, Oikonomou E, Khunte A, Miller E, Khera R. Detection of ATTR cardiac amyloidosis using a novel artificial intelligence algorithm for wearable-adapted noisy single-lead electrocardiograms. European Heart Journal 2024, 45: ehae666.3438. DOI: 10.1093/eurheartj/ehae666.3438.Peer-Reviewed Original ResearchReal-world noiseSingle-lead ECGArtificial intelligence algorithmsMultiple signal-to-noise ratiosCommunity-dwelling adultsSignal-to-noise ratioIntelligence algorithmsATTR-CMMatched controlsECG signalsDevelopment cohortPreventive careHealthcare servicesBlack adultsHospital systemCommunity screeningAlgorithmBone scintigraphy scansATTR cardiac amyloidosisPrevalence levelsOnset of symptomsPositive predictive valuePrevalenceAI-ECG algorithmSex-matched