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Doctor Evangelos K Oikonomou

Yale School of Medicine, New Haven (United States of America)

Member of:

European Society of Cardiology
Heart Failure Association of the ESC

Evangelos K. Oikonomou MD DPhil is a clinical investigator at the Yale School of Medicine and the Yale Cardiovascular Data Science (CarDS) Lab with a focus on AI in cardiovascular imaging, digital biomarkers, and the development of scalable technologies for the point-of-care screening of cardiovascular disease. He serves as an Associate Editor in European Heart Journal.

Presentations Events Articles Podcasts

Targeted deployment of AI-ECG for efficient screening of transthyretin amyloid cardiomyopathy using deep learning representations of longitudinal electronic health records

Event: ESC Congress 2025

Topic: Infiltrative Myocardial Disease

Session: Transthyretin cardiac amyloidosis

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Guiding the targeted deployment of AI-ECG for the precision diagnosis of structural heart disorders in the electronic health record

Event: ESC Congress 2025

Topic: Multimodal

Session: Artificial intelligence guiding clinical diagnosis: from imaging to ECG

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Automated radiomic profiling of epicardial adiposity for heart failure risk stratification: a multi-center study

Event: ESC Congress 2025

Topic: Imaging of Heart Failure

Session: Cardiac computed tomography innovations transforming cardiac care

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Real-world evaluation of an algorithmic machine-learning-guided testing approach in stable chest pain: a multinational, multicohort study

Event: ESC Congress 2025

Topic: e-Cardiology/Digital Health

Session: Best of European Heart Journal - Digital Health

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Foundation models bridging ECGs and electronic health records

Event: ESC Congress 2025

Topic: Large Language Model

Session: How large language models disrupt cardiovascular clinical care

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Multimodal screening of transthyretin amyloid cardiomyopathy through artificial intelligence applied to electrocardiographic images and point-of-care ultrasound: a multi-center study

Event: Heart Failure 2025

Topic: Clinical

Session: ePosters in myocardial disease (2)

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Artificial intelligence applied to electrocardiographic images for the risk stratification of cancer therapeutics-related cardiac dysfunction

Event: ESC Congress 2024

Topic: Cardio-Oncology

Session: Cardiovascular risk of cancer therapy

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Deep learning to predict progression of aortic stenosis

Event: ESC Congress 2024

Topic: Aortic Valve Stenosis

Session: Digital tools to inform decisions in aortic stenosis

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Artificial intelligence-guided screening of under-recognized cardiomyopathies adapted for point-of-care echocardiography

Event: ESC Congress 2024

Topic: Myocardial Disease

Session: Imaging to improve diagnosis and risk-stratification of cardiomyopathies

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Characterizing the progression of subclinical cardiac amyloidosis through artificial intelligence applied to electrocardiographic images and echocardiograms

Event: ESC Congress 2024

Topic: Infiltrative Myocardial Disease

Session: Cardiac amyloidosis: how to stage and score

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