Aline Pedroso, PhD
Associate Research ScientistAbout
Titles
Associate Research Scientist
Lead, Scientific Operations, Cardiovascular Data Science (CarDS) Lab
Biography
Dr. Aline Pedroso is a pharmacist and epidemiologist and is the Lead for Scientific Operations at the Cardiovascular Data Science (CarDS) Lab at the Yale School of Medicine. Her research focuses on large-scale studies on cardiovascular risk assessment, particularly in low-resource settings. She also works on studying existing and emerging practices and health policies and their effectiveness in improving patient outcomes. In addition, as the operations lead at the CarDS Lab, she is involved in the design and execution of multicenter studies that deploy digital health and artificial intelligence tools for improving the detection and prognostication of cardiovascular diseases. She manages a broad research portfolio at the CarDS Lab working with a large interdisciplinary team of clinician-scientists and data scientists for the design of innovative health technologies, and manages partnerships with academic, pharmaceutical, and industry partners.
Last Updated on June 02, 2025.
Departments & Organizations
- All Institutions
- Internal Medicine
Education & Training
- Postdoctoral Research Associate
- Cardiovascular Data Science (CarDS) Lab (2024)
- PhD
- Federal University of Sao Joao del Rei, Health Sciences (2024)
- Postgraduate Associate
- Cardiovascular Data Science (CarDS) Lab (2023)
- MS
- Federal University of Sao Joal del Rei, Health Sciences (2019)
- BSc
- Federal University of Vales do Jequitinhonha e Mucuri, Pharmacy (2014)
Research
Publications
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 cohortReferralA 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 zipFollow-Up Assessment of Adherence to Methodological Standards in National Inpatient Sample Research
Dhingra L, Pedroso A, Aminorroaya A, Caraballo C, Mahajan S, Bansal B, Krumholz H, Khera R. Follow-Up Assessment of Adherence to Methodological Standards in National Inpatient Sample Research. JAMA Network Open 2026, 9: e2555753. PMID: 41591780, PMCID: PMC12848622, DOI: 10.1001/jamanetworkopen.2025.55753.Peer-Reviewed Original Research
2025
Evaluating the Accessibility of Transcatheter and Surgical Aortic Valve Replacement Across the US Via Driving-Times
Kapadia S, Shen M, Hanna J, Wheelock K, Pedroso A, Vora A, Dhingra L, Aminorroaya A, Khera R. Evaluating the Accessibility of Transcatheter and Surgical Aortic Valve Replacement Across the US Via Driving-Times. The American Journal Of Cardiology 2025, 262: 61-67. PMID: 41475454, DOI: 10.1016/j.amjcard.2025.12.007.Peer-Reviewed Original ResearchConceptsSurgical aortic valve replacementTranscatheter aortic valve replacementAortic valve replacementTranscatheter aortic valve replacement centersValve replacementMinimally invasive alternativeMedian ageMedian driving timeInvasive alternativeTAVR centersZip codesDisadvantaged rural communitiesHighest proportionSociodemographic correlatesProportion of beneficiariesTranscatheterMixed-effects modelsLinear mixed-effects modelsRural communitiesCardiovascular risk stratification without recalibration: A comparative study of the PREVENT and WHO risk scores in a multiethnic Brazilian cohort
Pedroso A, Brant L, Ribeiro A, Barreto S, Figueiredo R, Khera R. Cardiovascular risk stratification without recalibration: A comparative study of the PREVENT and WHO risk scores in a multiethnic Brazilian cohort. American Journal Of Preventive Cardiology 2025, 25: 101392. PMID: 41613350, PMCID: PMC12849047, DOI: 10.1016/j.ajpc.2025.101392.Peer-Reviewed Original ResearchPopulation-based cohortNet reclassification indexPopulation-based cohort of adultsArea under the receiver operating characteristic curveASCVD riskRisk scoreCardiovascular risk scoreCohort of adultsMiddle-income countriesRisk stratificationCardiovascular risk factorsWHO risk scorePrevention scoreAccurate risk stratificationReceiver operating characteristic curveASCVD eventsRisk ratioLMICsCardiovascular risk stratificationOperating characteristics curveDiverse populationsPrevention modelRisk factorsASCVDRisk reclassificationMultinational assessment of traditional and AI-electrocardiography based risk prediction for heart failure in prospective cohort studies
Pedroso A, Dhingra L, Aminorroaya A, Figueiredo R, Brant L, Barreto S, Ribeiro A, Khera R. Multinational assessment of traditional and AI-electrocardiography based risk prediction for heart failure in prospective cohort studies. European Heart Journal 2025, 46 DOI: 10.1093/eurheartj/ehaf784.1053.Peer-Reviewed Original ResearchELSA-BrasilPCP-HFProspective cohort studyStructural heart disordersHF riskTraditional risk scoresRisk scoreCommunity-based prospective cohort studyHF eventsRisk predictionCohort studyHazard ratioHF risk predictionHF risk stratificationCox proportional survival analysisHigh-income populationsMiddle-income populationsHF risk scoreAggressive risk reductionReclassification of riskClinical decision-makingUK BiobankRisk stratificationIncident HFRisk tertilesTargeted deployment of AI-ECG for efficient screening of transthyretin amyloid cardiomyopathy using deep learning representations of longitudinal electronic health records
Oikonomou E, Dhingra L, Batinica B, Coppi A, Malicki C, Pedroso A, Khera R. Targeted deployment of AI-ECG for efficient screening of transthyretin amyloid cardiomyopathy using deep learning representations of longitudinal electronic health records. European Heart Journal 2025, 46 DOI: 10.1093/eurheartj/ehaf784.2685.Peer-Reviewed Original ResearchElectronic health recordsDeep learning representationsLongitudinal electronic health recordsHealth systemHealth recordsIndividual electronic health recordsOptimal decision thresholdIndividuals seeking careOpportunistic deploymentTargeted deploymentDeep learningHigh precisionOptimal deploymentTraining setDownstream testingHealthcare encountersMultimodal pipelinePositive screenDecision thresholdDeploymentATTR-CMOptimal intersectionDevelopment setHealthRepresentationPerformance of the PREVENT risk score for atherosclerotic cardiovascular disease in a diverse population-based cohort study: comparative assessment against the recalibrated WHO CVD risk score
Pedroso A, Brant L, Ribeiro A, Barreto S, Figueiredo R, Khera R. Performance of the PREVENT risk score for atherosclerotic cardiovascular disease in a diverse population-based cohort study: comparative assessment against the recalibrated WHO CVD risk score. European Heart Journal 2025, 46 DOI: 10.1093/eurheartj/ehaf784.3502.Peer-Reviewed Original ResearchCommunity-based cohortWorld Health OrganizationAtherosclerotic cardiovascular diseaseRisk scoreRisk of atherosclerotic cardiovascular diseaseNet reclassification indexPopulation-based cohort studyCardiovascular risk prediction modelsCVD risk scoreAtherosclerotic cardiovascular disease eventsIdentification of high-risk individualsDiverse populationsELSA-Brasil cohortModel discriminationAtherosclerotic cardiovascular disease riskCardiovascular risk scoreSubgroups of sexCardiovascular diseaseMiddle-income countriesWorld Health Organization scoreHigh-risk individualsYears of follow-upRisk prediction modelHigher-risk categoriesLMIC settingsElectrocardiographic age as a predictor of cardiovascular events in Brazilian adults: from the ELSA-Brasil study
Ciminelli A, Pinto-Filho M, Camelo L, Pedroso A, Menezes S, Giatti L, Barreto S, Ribeiro A, Ribeiro A, Brant L. Electrocardiographic age as a predictor of cardiovascular events in Brazilian adults: from the ELSA-Brasil study. European Heart Journal 2025, 46 DOI: 10.1093/eurheartj/ehaf784.4406.Peer-Reviewed Original ResearchBrazilian adultsELSA-BrasilCardiovascular diseaseHigher CVD riskCardiovascular outcomesELSA-Brasil studyRisk factorsPrimary prevention strategiesIncidence curvesPrevalent cardiovascular diseaseCommunity-based cohortCox proportional hazards modelsCardiovascular risk factorsRisk prediction scoreTraditional cardiovascular risk factorsIncomplete outcome dataRisk of mortalityLevel of educationNo significant associationProportional hazards modelCox proportional modelsCVD riskCardiovascular healthFine-Gray modelCardiovascular events
Academic Achievements & Community Involvement
News
News
- January 23, 2025
New AI Tool Identifies Risk of Future Heart Failure
- November 05, 2024
Yale Researchers at American Heart Association Scientific Session 2024
- August 26, 2024
Which Diabetes Meds Are Best for Reducing Heart Attack and Stroke Risk?
- April 01, 2024
Yale Faculty Present Groundbreaking Clinical Research at the 2024 American College of Cardiology Scientific Sessions
Get In Touch
Contacts
Lab Number
Locations
CarDS Lab
Academic Office
195 Church Street, Fl 6th
New Haven, CT 06510