2024
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 AS
2023
SMART-AS: A NOVEL ARTIFICIAL INTELLIGENCE TOOL TO DETECT SEVERE AORTIC STENOSIS FROM ELECTROCARDIOGRAPHIC IMAGES
Sangha V, Oikonomou E, Khunte A, Gupta K, Mortazavi B, Khera R. SMART-AS: A NOVEL ARTIFICIAL INTELLIGENCE TOOL TO DETECT SEVERE AORTIC STENOSIS FROM ELECTROCARDIOGRAPHIC IMAGES. Journal Of The American College Of Cardiology 2023, 81: 2409. DOI: 10.1016/s0735-1097(23)02853-x.Peer-Reviewed Original Research
2022
Automated multilabel diagnosis on electrocardiographic images and signals
Sangha V, Mortazavi BJ, Haimovich AD, Ribeiro AH, Brandt CA, Jacoby DL, Schulz WL, Krumholz HM, Ribeiro ALP, Khera R. Automated multilabel diagnosis on electrocardiographic images and signals. Nature Communications 2022, 13: 1583. PMID: 35332137, PMCID: PMC8948243, DOI: 10.1038/s41467-022-29153-3.Peer-Reviewed Original ResearchConceptsConvolutional neural networkArtificial intelligenceApplication of AISignal-based dataSignal-based modelElectrocardiographic imagesECG imagesGrad-CAMImage-based modelsNeural networkDiagnosis modelECG signalsImagesClinical labelsValidation setLabelsExternal validation setMultilabelIntelligenceNetworkApplicationsModelBroad useSetBroader setting