Bruno Batinica
Postdoctoral AssociateAbout
Research
Publications
2026
26-A-12260-ACC SINGLE-LEAD ECG-AGE FROM WEARABLES AS A DEVICE-AGNOSTIC DIGITAL BIOMARKER OF CARDIOVASCULAR RISK: MULTISITE AND PROSPECTIVE VALIDATION
Dhingra L, Batinica B, Croon P, Aminorroaya A, Shankar S, Brant L, Barreto S, Ribeiro A, Pedroso A, Oikonomou E, Khera R. 26-A-12260-ACC SINGLE-LEAD ECG-AGE FROM WEARABLES AS A DEVICE-AGNOSTIC DIGITAL BIOMARKER OF CARDIOVASCULAR RISK: MULTISITE AND PROSPECTIVE VALIDATION. Journal Of The American College Of Cardiology 2026, 87: a1208-a1209. DOI: 10.1016/j.jacc.2026.02.2971.Peer-Reviewed Original Research26-A-19569-ACC DEVELOPMENT AND MULTINATIONAL VALIDATION OF ARTIFICIAL INTELLIGENCE-ENABLED ASCVD RISK STRATIFICATION USING ELECTROCARDIOGRAMS
Batinica B, Oikonomou E, Dhingra L, Pedroso A, Aminorroaya A, Biswas D, Khera R. 26-A-19569-ACC DEVELOPMENT AND MULTINATIONAL VALIDATION OF ARTIFICIAL INTELLIGENCE-ENABLED ASCVD RISK STRATIFICATION USING ELECTROCARDIOGRAMS. Journal Of The American College Of Cardiology 2026, 87: a225-a226. DOI: 10.1016/j.jacc.2026.02.557.Peer-Reviewed Original ResearchArtificial 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 assessmentCohortPopulation-level cardiovascular risk prediction models including biochemical predictors in 800 000 individuals
Batinica B, Mehta S, Liang J, Jackson R, Poppe K. Population-level cardiovascular risk prediction models including biochemical predictors in 800 000 individuals. European Heart Journal Open 2026, 6: oeag051. PMID: 42125027, PMCID: PMC13160000, DOI: 10.1093/ehjopen/oeag051.Peer-Reviewed Original ResearchTARGET-AI: A Foundational Approach for the Targeted Deployment of Artificial Intelligence Electrocardiography in the Electronic Health Record
Oikonomou E, Batinica B, Dhingra L, Aminorroaya A, Coppi A, Khera R. TARGET-AI: A Foundational Approach for the Targeted Deployment of Artificial Intelligence Electrocardiography in the Electronic Health Record. NEJM AI 2026, 3 DOI: 10.1056/aioa2500588.Peer-Reviewed Original Research
2025
Targeted 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 setHealthRepresentationGuiding the targeted deployment of AI-ECG for the precision diagnosis of structural heart disorders in the electronic health record
Oikonomou E, Batinica B, Dhingra L, Aminorroaya A, Coppi A, Khera R. Guiding the targeted deployment of AI-ECG for the precision diagnosis of structural heart disorders in the electronic health record. European Heart Journal 2025, 46 DOI: 10.1093/eurheartj/ehaf784.4470.Peer-Reviewed Original ResearchElectronic health recordsHealth recordsF1 scoreElectrocardiogram imageEHR eventContrastive Language-Image Pre-trainingTest setDeep learning representationsFalse positive screensLongitudinal EHR dataStructural heart disordersBalance of precisionLearned representationsTrained embeddingsImage encoderVision TransformerUK BiobankHealth systemEHR dataPositive screenAlgorithmic pipelinePre-trainingAI-ECGDeploymentHeart diseaseTransforming 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 ResearchConceptsAtherosclerotic 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 disease
2023
Cardiovascular risk prediction in a New Zealand cohort of patients with known cardiovascular disease - a regional individual patient-level data linkage study
Holt A, Batinica B, Liang J, Lamberts M, Jackson R, Poppe K. Cardiovascular risk prediction in a New Zealand cohort of patients with known cardiovascular disease - a regional individual patient-level data linkage study. European Heart Journal 2023, 44: ehad655.3002. DOI: 10.1093/eurheartj/ehad655.3002.Peer-Reviewed Original ResearchDevelopment and validation of cardiovascular risk prediction equations in 76 000 people with known cardiovascular disease
Holt A, Batinica B, Liang J, Kerr A, Crengle S, Hudson B, Wells S, Harwood M, Selak V, Mehta S, Grey C, Lamberts M, Jackson R, Poppe K. Development and validation of cardiovascular risk prediction equations in 76 000 people with known cardiovascular disease. European Journal Of Preventive Cardiology 2023, 31: 218-227. PMID: 37767960, DOI: 10.1093/eurjpc/zwad314.Peer-Reviewed Original Research