Lovedeep Singh Dhingra, MBBS, MHS
Associate Research ScientistAbout
Research
Publications
Featured Publications
Heart failure risk stratification using artificial intelligence applied to electrocardiogram images: a multinational study
Dhingra L, Aminorroaya A, Sangha V, Pedroso A, Asselbergs F, Brant L, Barreto S, Ribeiro A, Krumholz H, Oikonomou E, Khera R. Heart failure risk stratification using artificial intelligence applied to electrocardiogram images: a multinational study. European Heart Journal 2025, 46: 1044-1053. PMID: 39804243, PMCID: PMC12086686, DOI: 10.1093/eurheartj/ehae914.Peer-Reviewed Original ResearchYale New Haven Health SystemELSA-BrasilPCP-HFUK BiobankHF riskBrazilian Longitudinal Study of Adult HealthLongitudinal Study of Adult HealthBrazilian Longitudinal StudyRisk of new-onset HFPooled Cohort EquationsPrimary HF hospitalizationsHigher HF riskHarrell's C-statisticRisk of deathNew-onset HFCohort EquationsHealth systemComprehensive clinical evaluationAdult HealthHeart failureIncident HFHF hospitalizationBaseline HFC-statisticPrevent HFEnsemble Deep Learning Algorithm for Structural Heart Disease Screening Using Electrocardiographic Images PRESENT SHD
Dhingra L, Aminorroaya A, Sangha V, Pedroso A, Shankar S, Coppi A, Foppa M, Brant L, Barreto S, Ribeiro A, Krumholz H, Oikonomou E, Khera R. Ensemble Deep Learning Algorithm for Structural Heart Disease Screening Using Electrocardiographic Images PRESENT SHD. Journal Of The American College Of Cardiology 2025, 85: 1302-1313. PMID: 40139886, PMCID: PMC12199746, DOI: 10.1016/j.jacc.2025.01.030.Peer-Reviewed Original ResearchConceptsStructural heart diseaseYale-New Haven HospitalTransthoracic echocardiogramRisk stratificationHeart failureLeft-sided valvular diseaseSevere left ventricular hypertrophyLeft ventricular ejection fractionReceiver-operating characteristic curveVentricular ejection fractionLeft ventricular hypertrophyHeart disease screeningELSA-BrasilEnsemble deep learning algorithmRisk of deathConvolutional neural network modelEjection fractionEnsemble deep learning approachVentricular hypertrophyDeep learning algorithmsNew Haven HospitalDeep learning approachValvular diseaseNeural network modelClinical cohortArtificial Intelligence–Enabled Prediction of Heart Failure Risk From Single-Lead Electrocardiograms
Dhingra L, Aminorroaya A, Pedroso A, Khunte A, Sangha V, McIntyre D, Chow C, Asselbergs F, Brant L, Barreto S, Ribeiro A, Krumholz H, Oikonomou E, Khera R. Artificial Intelligence–Enabled Prediction of Heart Failure Risk From Single-Lead Electrocardiograms. JAMA Cardiology 2025, 10: 574-584. PMID: 40238120, PMCID: PMC12004248, DOI: 10.1001/jamacardio.2025.0492.Peer-Reviewed Original ResearchYale New Haven Health SystemELSA-BrasilPCP-HFNew-onset HFHarrell's C-statisticProspective population-based cohortUK Biobank (UKBBrazilian Longitudinal StudyELSA-Brasil participantsC-statisticPopulation-based cohortIntegrated discrimination improvementReclassification improvementRisk of deathUKB participantsHealth systemRetrospective cohort studyDiscrimination improvementMain OutcomesLeft ventricular systolic dysfunctionHF riskUKBCohort studySingle-lead ECGIndependent of ageUse of Wearable Devices in Individuals With or at Risk for Cardiovascular Disease in the US, 2019 to 2020
Dhingra L, Aminorroaya A, Oikonomou E, Nargesi A, Wilson F, Krumholz H, Khera R. Use of Wearable Devices in Individuals With or at Risk for Cardiovascular Disease in the US, 2019 to 2020. JAMA Network Open 2023, 6: e2316634. PMID: 37285157, PMCID: PMC10248745, DOI: 10.1001/jamanetworkopen.2023.16634.Peer-Reviewed Original ResearchConceptsHealth Information National Trends SurveyUS adultsExacerbate disparitiesWearable device usersCardiovascular diseaseCardiovascular healthPopulation-based cross-sectional studySelf-reported cardiovascular diseaseCardiovascular disease risk factorsNational Trends SurveyOverall US adult populationCardiovascular risk factor profileSelf-reported accessAssociated with lower useUse of wearable devicesImprove cardiovascular healthLower household incomeLower educational attainmentUS adult populationRisk factor profileNationally Representative SampleCross-sectional studyProportion of adultsTrends SurveyWearable device dataMultinational patterns of second line antihyperglycaemic drug initiation across cardiovascular risk groups: federated pharmacoepidemiological evaluation in LEGEND-T2DM
Khera R, Dhingra L, Aminorroaya A, Li K, Zhou J, Arshad F, Blacketer C, Bowring M, Bu F, Cook M, Dorr D, Duarte-Salles T, DuVall S, Falconer T, French T, Hanchrow E, Horban S, Lau W, Li J, Liu Y, Lu Y, Man K, Matheny M, Mathioudakis N, McLemore M, Minty E, Morales D, Nagy P, Nishimura A, Ostropolets A, Pistillo A, Posada J, Pratt N, Reyes C, Ross J, Seager S, Shah N, Simon K, Wan E, Yang J, Yin C, You S, Schuemie M, Ryan P, Hripcsak G, Krumholz H, Suchard M. Multinational patterns of second line antihyperglycaemic drug initiation across cardiovascular risk groups: federated pharmacoepidemiological evaluation in LEGEND-T2DM. BMJ Medicine 2023, 2: e000651. PMID: 37829182, PMCID: PMC10565313, DOI: 10.1136/bmjmed-2023-000651.Peer-Reviewed Original ResearchType 2 diabetes mellitusSecond-line treatmentCardiovascular risk groupsDiabetes mellitusCardiovascular diseaseAntihyperglycaemic drugsLine treatmentRisk groupsObservational Health Data SciencesGlucagon-like peptide-1 receptor agonistsElectronic health recordsSodium-glucose cotransporter 2 inhibitorsCalendar year trendsPeptide-1 receptor agonistsUS databaseOutcomes of patientsCotransporter 2 inhibitorsAdministrative claims databaseSecond-line drugsHealth recordsSodium-glucose cotransporter-2 inhibitorsMedication useMetformin monotherapyGuideline recommendationsOutcome measuresCardiovascular Care Innovation through Data-Driven Discoveries in the Electronic Health Record
Dhingra L, Shen M, Mangla A, Khera R. Cardiovascular Care Innovation through Data-Driven Discoveries in the Electronic Health Record. The American Journal Of Cardiology 2023, 203: 136-148. PMID: 37499593, PMCID: PMC10865722, DOI: 10.1016/j.amjcard.2023.06.104.Peer-Reviewed Reviews, Practice Guidelines, Standards, and Consensus StatementsConceptsElectronic health recordsData elementsUnstructured data streamsUnstructured data elementsNatural language processingCommon data modelHealth recordsStructured data elementsComputer visionUnstructured dataData streamsHeterogeneity challengesSeamless deliveryData modelLanguage processingData storageFree textClinical narrativesComputational phenotypesOngoing workPatient informationRapid innovationSpecific expertiseConfidentialityOngoing innovation
2026
Artificial Intelligence-enhanced Electrocardiography for Heart Failure Screening and Risk Stratification
Dhingra L, Croon P, Batinica B, Aminorroaya A, Pedroso A, Khera R. Artificial Intelligence-enhanced Electrocardiography for Heart Failure Screening and Risk Stratification. Current Heart Failure Reports 2026, 23: 10. PMID: 41838300, DOI: 10.1007/s11897-026-00748-x.Peer-Reviewed Original ResearchRisk factor surveillancePublic health challengeHeart failure screeningHF risk assessmentHF screeningRoutine careCommunity programsHF riskHealth challengesECG testRisk scoreECG interpretationRisk stratificationConfirmatory imagingSymptom onsetRiskCost-effectiveClinical implementationProspective validationScreeningTherapy decisionsFunctional abnormalitiesCareRisk assessmentCohortArtificial intelligence-enabled electrocardiography to triage echocardiography for structural heart disease diagnosis in a low-resource setting
Pedroso A, Nascimento B, Dhingra L, Shankar S, Vinhal W, Borges e Reges R, Cardoso C, Sable C, Ribeiro A, Khera R. Artificial intelligence-enabled electrocardiography to triage echocardiography for structural heart disease diagnosis in a low-resource setting. American Journal Of Preventive Cardiology 2026, 101539. DOI: 10.1016/j.ajpc.2026.101539.Peer-Reviewed Original ResearchPoint-of-care ultrasoundLow-resource settingsStructural heart diseaseMajor ECG abnormalityScreening cohortAI-ECGCardiovascular screening programHealth system impactTransthoracic echocardiographyECG abnormalitiesReferral workflowsIdentification of structural heart diseaseDiagnosis of structural heart diseaseComprehensive transthoracic echocardiographyReferral thresholdsScreening programScreened referencesReferral strategiesDecision-curve analysisIdentification of individualsPositive predictive valueStandard referralECG interpretationImaging cohortReferralArtificial intelligence-based automated interpretation of images of electrocardiograms: development and multinational validation of ECG-GPT
Khunte A, Sangha V, Oikonomou E, Dhingra L, Aminorroaya A, Coppi A, Shankar S, Rockers E, Mortazavi B, Bhatt D, Krumholz H, Al-Kindi S, Nadkarni G, Vaid A, Khera R. Artificial intelligence-based automated interpretation of images of electrocardiograms: development and multinational validation of ECG-GPT. European Heart Journal - Digital Health 2026, 7: ztag031. PMID: 41853639, PMCID: PMC12993923, DOI: 10.1093/ehjdh/ztag031.Peer-Reviewed Original ResearchBundle branch blockEncoder-decoder modelBranch blockFascicular blockUS health systemClinical assessmentLeft anterior fascicular blockRight bundle branch blockLeft posterior fascicular blockAssessment of electrocardiogramsLeft bundle branch blockAnterior fascicular blockPosterior fascicular blockPremature atrial contractionsPremature ventricular contractionsHealth systemPTB-XL datasetLow-resource settingsAtrioventricular blockConduction abnormalitiesSinus bradycardiaAtrial contractionSinus tachycardiaAtrial fibrillationDiagnosis statementsA real-world evaluation of longitudinal healthcare expenses in a health system registry of type-2 diabetes mellitus and cardiovascular disease enabled by the 21st century cures act
Dhingra L, Pedroso A, Aminorroaya A, Rajpura J, Mehanna S, Tonnu-Mihara I, Khera R. A real-world evaluation of longitudinal healthcare expenses in a health system registry of type-2 diabetes mellitus and cardiovascular disease enabled by the 21st century cures act. American Journal Of Preventive Cardiology 2026, 25: 101425. PMID: 41767452, PMCID: PMC12946900, DOI: 10.1016/j.ajpc.2026.101425.Peer-Reviewed Original ResearchFinancial hardshipHealthcare expensesObservational cohort studyHealthcare eventsHealthcare spendingPrevalence of financial hardshipAtherosclerotic cardiovascular diseaseYale New Haven Health SystemDiverse cohortDiverse cohort of individualsReal world evaluationCardiovascular diseaseMedian household incomeUS Census dataCohort study of patientsMultivariate logistic regressionCohort of individualsHealthcare visitsRegular careObservational cohort study of patientsHealth systemT2D diagnosisType 2 diabetes mellitusOutpatient networkResidential zip
Academic Achievements & Community Involvement
News
News
- March 16, 2026
Yale School of Medicine Faculty To Present New Cardiovascular Research at National Cardiology Conference
- February 11, 2026
Using AI to Guide AI
- January 23, 2025
New AI Tool Identifies Risk of Future Heart Failure
- November 05, 2024
Yale Researchers at American Heart Association Scientific Session 2024