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 ASEfficient deep learning-based automated diagnosis from echocardiography with contrastive self-supervised learning
Holste G, Oikonomou E, Mortazavi B, Wang Z, Khera R. Efficient deep learning-based automated diagnosis from echocardiography with contrastive self-supervised learning. Communications Medicine 2024, 4: 133. PMID: 38971887, PMCID: PMC11227494, DOI: 10.1038/s43856-024-00538-3.Peer-Reviewed Original ResearchSelf-supervised learningTransfer learningTraining dataEchocardiogram videosPortion of labelled dataStandard transfer learning approachContrastive self-supervised learningSelf-supervised learning approachLearning approachImage recognition tasksState-of-the-artContrastive learning approachFine-tuningTransfer learning approachMedical image diagnosisCardiac disease diagnosisContrastive learningVideo framesLabeled datasetLabeled dataExpert labelsClassification performanceMedical imagesRecognition taskVideo