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INFORMATION FOR

    Evangelos K. Oikonomou, MD, DPhil

    Clinical Fellow
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    Education

    DPhil
    University of Oxford (2020)


    MD
    University of Athens School of Health Sciences (2015)


    Training

    Clinical fellow
    Yale School of Medicine (2025)


    Post-doctoral fellow
    Yale School of Medicine (2025)


    About

    Titles

    Clinical Fellow

    Biography

    Evangelos (Evan) Oikonomou is a clinical fellow in cardiovascular medicine, a post-doctoral research fellow in the Cardiovascular Data Science (CarDS) lab, and a member of the ABIM Physician-Scientist Research Pathway at Yale. His work focuses on the intersection of applied computer vision and statistical machine learning, with a specific focus on developing tools for the improved phenotyping of cardiovascular disease using scalable approaches that can be deployed at minimal cost using existing care pathways. He graduated as valedictorian of his class from the University of Athens Medical School in Greece, before pursuing a Ph.D. (D.Phil.) degree at the University of Oxford, where he was recognized with the Radcliffe Department of Medicine Graduate Prize for his scientific work. In 2019 he joined the Physician-Scientist Training Program at the Yale School of Medicine, and he has since completed his internal medicine residency and his core clinical fellowship in cardiology.

    He is a recipient of an F32 NRSA fellowship award from NHLBI (National Institutes of Health), and his work has been recognized through numerous Young Investigator Awards sponsored by the American Heart Association, American College of Cardiology, Northwestern Cardiovascular Young Investigator Forum, the European Society of Cardiology and European Association of Preventive Cardiology.

    He has led a broad portfolio in applied artificial intelligence in cardiovascular and cardiometabolic medicine. First, he has defined and translated a key interplay between the perivascular adipose tissue and vascular inflammation in humans into a clinically actionable algorithmic tool that can refine cardiovascular risk on routine cardiac CT scans. Second, he has developed and validated deep learning algorithms for the efficient diagnosis of common and rare cardiomyopathies specifically adapted for point-of-care echocardiography. Finally, he has led an extensive body of work on defining treatment effect heterogeneity across clinical trials, with direct implications for evidence translation and the design of new adaptive trials with data-driven predictive enrichment.

    His work has been published in several peer-reviewed journals, including the Lancet, Lancet Digital Health, European Heart Journal, JACC, Circulation, JAMA Cardiology, Diabetes Care.

    A detailed list of Dr. Oikonomou's publications can be found here: https://www.ncbi.nlm.nih.gov/myncbi/evangelos.oikonomou.1/bibliography/public/ and https://scholar.google.com/citations?user=GgJv1SMAAAAJ&hl=en

    Departments & Organizations

    Education & Training

    Clinical fellow
    Yale School of Medicine (2025)
    Post-doctoral fellow
    Yale School of Medicine (2025)
    Resident
    Yale School of Medicine (2021)
    Intern
    Yale School of Medicine (2020)
    DPhil
    University of Oxford (2020)
    MD
    University of Athens School of Health Sciences (2015)

    Board Certifications

    • Internal Medicine

      Certification Organization
      ABIM
      Original Certification Date
      2022

    Research

    Overview

    Medical Research Interests

    Adaptive Clinical Trial; Adipose Tissue; Artificial Intelligence; Cardiovascular Diseases; Computed Tomography Angiography; Echocardiography; Machine Learning; Multimodal Imaging

    Research at a Glance

    Research Interests

    Research topics Evangelos K. Oikonomou is interested in exploring.

    Publications

    Featured Publications

    Academic Achievements & Community Involvement

    • activity

      European Heart Journal

    • activity

      AI-Enabled Diagnostic and Prognostic Biomarkers in Echocardiography

    • activity

      Scalable AI biomarkers for echocardiography to enable prediction, diagnosis, and prognostication: A JAMA session

    • activity

      AI applied to ECG images for the risk stratification of cancer therapeutics-related cardiac dysfunction

    • activity

      AI-guided screening of cardiomyopathies using POCUS

    Get In Touch

    Contacts

    Mailing Address

    Yale School of Medicine

    195 Church St, 6th floor

    New Haven, CT 06510

    United States