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 ASOPTIMIZING PHENOTYPING ALGORITHMS FOR IDENTIFYING PULMONARY EMBOLISM IN ELECTRONIC DATABASES: THE MULTICENTER PE-EHR+ STUDY
Bikdeli B, Bejjani A, Lo Y, Khairani C, Mahajan S, Secemsky E, Jimenez J, Aghayev A, Hunsaker A, Wang L, Hussain M, Appah-Sampong A, Mojibian H, Lin Z, Aneja S, Barco S, Klok F, Konstantinides S, Zhou L, Monreal M, Jimenez D, Piazza G, Krumholz H. OPTIMIZING PHENOTYPING ALGORITHMS FOR IDENTIFYING PULMONARY EMBOLISM IN ELECTRONIC DATABASES: THE MULTICENTER PE-EHR+ STUDY. Journal Of The American College Of Cardiology 2024, 83: 2108. DOI: 10.1016/s0735-1097(24)04098-1.Peer-Reviewed Original ResearchPhenotyping algorithmsAlgorithm
2023
Developing Validated Tools to Identify Pulmonary Embolism in Electronic Databases: Rationale and Design of the PE-EHR+ Study
Bikdeli B, Lo Y, Khairani C, Bejjani A, Jimenez D, Barco S, Mahajan S, Caraballo C, Secemsky E, Klok F, Hunsaker A, Aghayev A, Muriel A, Wang Y, Hussain M, Appah-Sampong A, Lu Y, Lin Z, Aneja S, Khera R, Goldhaber S, Zhou L, Monreal M, Krumholz H, Piazza G. Developing Validated Tools to Identify Pulmonary Embolism in Electronic Databases: Rationale and Design of the PE-EHR+ Study. Thrombosis And Haemostasis 2023, 123: 649-662. PMID: 36809777, PMCID: PMC11200175, DOI: 10.1055/a-2039-3222.Peer-Reviewed Original ResearchConceptsElectronic health recordsNLP algorithmNatural language processing toolsLanguage processing toolsPrincipal discharge diagnosisICD-10 codesDischarge diagnosisNLP toolsChart reviewHealth systemProcessing toolsYale New Haven Health SystemPatient identificationElectronic databasesHealth recordsData validationHigh-risk PEPulmonary Embolism ResearchSecondary discharge diagnosisIdentification of patientsManual chart reviewNegative predictive valueCodeRadiology reportsAlgorithm