2025
Transforming Population Health Screening for Atherosclerotic Cardiovascular Disease with AI-Enhanced ECG Analytics: Opportunities and Challenges
Biswas D, Aminorroaya A, Croon P, Batinica B, Pedroso A, Khera R. Transforming Population Health Screening for Atherosclerotic Cardiovascular Disease with AI-Enhanced ECG Analytics: Opportunities and Challenges. Current Atherosclerosis Reports 2025, 27: 86. PMID: 40888973, DOI: 10.1007/s11883-025-01337-4.Peer-Reviewed Original ResearchMeSH KeywordsArtificial IntelligenceAtherosclerosisElectrocardiographyHumansMass ScreeningPopulation HealthRisk AssessmentConceptsAtherosclerotic cardiovascular diseasePopulation health screeningPopulation-level screeningCardiovascular diseaseLow riskHealth screeningStandard risk factorsHospital-basedCardiovascular healthSubclinical coronary artery diseaseWorkflow integrationSingle-lead ECGPersonalized interventionsPatient outcomesDiverse populationsTraditional risk modelsECG interpretationRisk factorsAscertainment biasImplementation challengesAdverse cardiovascular eventsProspective studyLogistical challengesRe-classifying patientsCoronary artery diseaseScientific Writing in the Era of Large Language Models: A Computational Analysis of AI- Versus Human-Created Content
Khera R, Pedroso A, Keloth V, Xu H, Silva G, Schwamm L. Scientific Writing in the Era of Large Language Models: A Computational Analysis of AI- Versus Human-Created Content. Stroke 2025, 56: 3078-3083. PMID: 40814778, DOI: 10.1161/strokeaha.125.051913.Peer-Reviewed Original ResearchConceptsLanguage modelArtificial intelligenceAI-generatedLinguistic featuresDetection toolsAI-generated contentHuman-written textLanguage perplexityHuman expertsPerformance of expertsLinguistic differencesScientific textsGrade levelWord countEssayLanguageScientific communicationScientific writingComputer synthesisHigher grade levelsTextScientific contentReadability scoresPerplexityFlesch-KincaidUso da Inteligência Artificial Aplicada ao Eletrocardiograma para Diagnóstico de Disfunção Sistólica Ventricular Esquerda
de Santana W, Pinto M, Barreto S, Foppa M, Giatti L, Khera R, Ribeiro A. Uso da Inteligência Artificial Aplicada ao Eletrocardiograma para Diagnóstico de Disfunção Sistólica Ventricular Esquerda. Arquivos Brasileiros De Cardiologia 2025, 122: e20240740. PMID: 40396866, PMCID: PMC12108124, DOI: 10.36660/abc.20240740.Peer-Reviewed Original ResearchConceptsLeft ventricular systolic dysfunctionLeft ventricular ejection fractionNegative predictive valueDiagnostic odds ratioPositive predictive valueHeart failureDetect left-ventricular systolic dysfunctionPredictive valueVentricular systolic dysfunctionVentricular ejection fractionNegative likelihood ratioPositive likelihood ratioDiagnostic accuracy cross-sectional studyLikelihood ratioCross-sectional studySystolic dysfunctionEjection fractionEvaluating HFAUC-ROCElectrocardiographic alterationsOdds ratioEchocardiogramROC curveScreening toolElectrocardiogramControversy in Hypertension: Pro-Side of the Argument Using Artificial Intelligence for Hypertension Diagnosis and Management
Armoundas A, Ahmad F, Attia Z, Doudesis D, Khera R, Kyriakoulis K, Stergiou G, Tang W. Controversy in Hypertension: Pro-Side of the Argument Using Artificial Intelligence for Hypertension Diagnosis and Management. Hypertension 2025, 82: 929-944. PMID: 40091745, PMCID: PMC12094096, DOI: 10.1161/hypertensionaha.124.22349.Peer-Reviewed Original ResearchMeSH KeywordsAntihypertensive AgentsArtificial IntelligenceBlood PressureDisease ManagementHumansHypertensionPrecision MedicineConceptsArtificial intelligenceHypertension diagnosisBlood pressure elevationRelationship to cardiovascular diseaseManagement of hypertensionLong-term managementArtificial intelligence-based solutionsPressure elevationPublic health challengeHypertensionArtificial intelligence scienceComplex pathogenesisClinical implementationCardiovascular diseaseState-of-artDiagnosisData-driven approachHypertension managementIntelligence scienceClinical adoptionArtificial Intelligence to Enhance Precision Medicine in Cardio-Oncology: A Scientific Statement From the American Heart Association
Khera R, Asnani A, Krive J, Addison D, Zhu H, Vasbinder A, Fleming M, Arnaout R, Razavi P, Okwuosa T, Nursing O. Artificial Intelligence to Enhance Precision Medicine in Cardio-Oncology: A Scientific Statement From the American Heart Association. Circulation Genomic And Precision Medicine 2025, 18: e000097. PMID: 39989357, PMCID: PMC12316026, DOI: 10.1161/hcg.0000000000000097.Peer-Reviewed Original ResearchMeSH KeywordsAmerican Heart AssociationArtificial IntelligenceCardio-OncologyCardiotoxicityCardiovascular DiseasesHumansMedical OncologyNeoplasmsPrecision MedicineUnited StatesConceptsCardiovascular riskLong-term cardiovascular riskImmune checkpoint inhibitorsRisk of cardiovascular diseaseBiomarkers of riskCardio-oncology careHeightened risk of cardiovascular diseasePrevalence of cancerCheckpoint inhibitorsAmerican Heart AssociationCardiovascular risk managementTargeted therapyTherapeutic optionsCancer groupNovel therapiesHeightened riskHeart AssociationCardio-OncologyEnhancing precision medicineAdvanced imagingCardiovascular diseaseCancerDiagnostic testsTherapyPatientsArtificial intelligence-guided detection of under-recognised cardiomyopathies on point-of-care cardiac ultrasonography: a multicentre study
Oikonomou E, Vaid A, Holste G, Coppi A, McNamara R, Baloescu C, Krumholz H, Wang Z, Apakama D, Nadkarni G, Khera R. Artificial intelligence-guided detection of under-recognised cardiomyopathies on point-of-care cardiac ultrasonography: a multicentre study. The Lancet Digital Health 2025, 7: e113-e123. PMID: 39890242, PMCID: PMC12084816, DOI: 10.1016/s2589-7500(24)00249-8.Peer-Reviewed Original ResearchConceptsYale New Haven Health SystemPoint-of-care ultrasonographyMount Sinai Health SystemTransthyretin amyloid cardiomyopathyArtificial intelligenceHealth systemAmyloid cardiomyopathyHypertrophic cardiomyopathyRetrospective cohort of individualsCardiomyopathy casesTesting artificial intelligenceConvolutional neural networkSinai Health SystemCohort of individualsOpportunistic screeningHypertrophic cardiomyopathy casesMulti-labelPositive screenAI frameworkEmergency departmentMortality riskNeural networkLoss functionCardiac ultrasonographyAugmentation approach
2024
Reviewer Experience Detecting and Judging Human Versus Artificial Intelligence Content: The Stroke Journal Essay Contest
Silva G, Khera R, Schwamm L, Acampa M, Adelman E, Boltze J, Broderick J, Brodtmann A, Christensen H, Dalli L, Duncan K, Elgendy I, Ergul A, Goldstein L, Hinkle J, Johansen M, Jood K, Kasner S, Levine S, Li Z, Lip G, Marsh E, Muir K, Ospel J, Pera J, Quinn T, Räty S, Ranta A, Richards L, Romero J, Willey J, Hillis A, Veerbeek J. Reviewer Experience Detecting and Judging Human Versus Artificial Intelligence Content: The Stroke Journal Essay Contest. Stroke 2024, 55: 2573-2578. PMID: 39224979, PMCID: PMC11529699, DOI: 10.1161/strokeaha.124.045012.Peer-Reviewed Original ResearchConceptsArtificial intelligenceEditorial board membersAuthor typeTraditional peer reviewLanguage modelIntelligent contentAuthor attributionGeneral textAI expertiseHuman authorityImproved accuracyAuthor's identityAuthor's manuscriptScientific journalsEssay contestPeer reviewPerception of qualityAuthorshipNature of authorshipIntelligenceLLMScientific writingScientific essayEssay qualityEssayAI-enabled diagnosis from an electrocardiogram image: the next frontier of innovation in a century-old technology
Khera R. AI-enabled diagnosis from an electrocardiogram image: the next frontier of innovation in a century-old technology. Heart 2024, 110: heartjnl-2024-324299. PMID: 39048290, PMCID: PMC11328242, DOI: 10.1136/heartjnl-2024-324299.Commentaries, Editorials and LettersTransforming Cardiovascular Care With Artificial Intelligence: From Discovery to Practice JACC State-of-the-Art Review
Khera R, Oikonomou E, Nadkarni G, Morley J, Wiens J, Butte A, Topol E. Transforming Cardiovascular Care With Artificial Intelligence: From Discovery to Practice JACC State-of-the-Art Review. Journal Of The American College Of Cardiology 2024, 84: 97-114. PMID: 38925729, PMCID: PMC12204085, DOI: 10.1016/j.jacc.2024.05.003.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsIntroducing the JAMA Summit
Bibbins-Domingo K, Angus D, Park H, Lewis R, Khera R, Zeis J, Flanagin A, Curfman G. Introducing the JAMA Summit. JAMA 2024, 331: 1451-1451. DOI: 10.1001/jama.2024.5570.Commentaries, Editorials and LettersArtificial intelligence-enhanced exposomics: novel insights into cardiovascular health
Khera R. Artificial intelligence-enhanced exposomics: novel insights into cardiovascular health. European Heart Journal 2024, 45: 1550-1552. PMID: 38544282, DOI: 10.1093/eurheartj/ehae159.Commentaries, Editorials and LettersConceptsCardiovascular health
2023
Automation Bias and Assistive AI
Khera R, Simon M, Ross J. Automation Bias and Assistive AI. JAMA 2023, 330: 2255-2257. PMID: 38112824, DOI: 10.1001/jama.2023.22557.Commentaries, Editorials and LettersMachine learning in precision diabetes care and cardiovascular risk prediction
Oikonomou E, Khera R. Machine learning in precision diabetes care and cardiovascular risk prediction. Cardiovascular Diabetology 2023, 22: 259. PMID: 37749579, PMCID: PMC10521578, DOI: 10.1186/s12933-023-01985-3.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsMeSH KeywordsArtificial IntelligenceCardiovascular DiseasesDiabetes MellitusHeart Disease Risk FactorsHumansMachine LearningRisk FactorsConceptsArtificial intelligence solutionsArtificial intelligence productsData-driven methodIntelligence solutionsArtificial intelligenceMachine learningPersonalized solutionsIntelligence productsBias mitigationMachineKey issuesPredictive modelSuch modelsSuccessful applicationRisk predictionParadigm shiftIntelligenceKey propertiesApplicationsLearningPersonalized careFrameworkSolutionCurrent regulatory frameworkHealthcareAI in Medicine—JAMA’s Focus on Clinical Outcomes, Patient-Centered Care, Quality, and Equity
Khera R, Butte A, Berkwits M, Hswen Y, Flanagin A, Park H, Curfman G, Bibbins-Domingo K. AI in Medicine—JAMA’s Focus on Clinical Outcomes, Patient-Centered Care, Quality, and Equity. JAMA 2023, 330: 818-820. PMID: 37566406, DOI: 10.1001/jama.2023.15481.Commentaries, Editorials and Letters
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
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