2024
Detection 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
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