Self-supervised representation learning reveals explainable physiological structure in high-dimensional magnetocardiography - Top-Institutions - MDSpire

Self-supervised representation learning reveals explainable physiological structure in high-dimensional magnetocardiography

  • By

  • Dominik D. Kranz

  • Oruç Kahriman

  • Dominic Dischl

  • Sascha Treskatsch

  • André Sander

  • Johannes Brachmann

  • Jai-Wun Park

  • Niels Wessel

  • June 1, 2026

  • 0 min

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Top Institutions in Cardiology

Brief introduction explaining scope and methodology.

  • #1

    Cleveland Clinic Heart, Vascular & Thoracic Institute
    Cleveland Clinic Heart, Vascular & Thoracic Institute

    Cleveland, Ohio

    Key Differentiators

    • Cardiology
    • Heart Surgery

  • #2

    Charité – Universitätsmedizin Berlin
    Charité – Universitätsmedizin Berlin

    Berlin, Germany

    Key Differentiators

    • Cardiology
    • Cardiac Diagnostics

  • #3

    University of Greifswald
    University of Greifswald

    Greifswald, Germany

    Key Differentiators

    • Cardiology
    • Data Access

  • #4

    University of Göttingen
    University of Göttingen

    Göttingen, Germany

    Key Differentiators

    • Cardiology
    • Data Analysis

  • #5

    Guangdong Provincial People’s Hospital
    Guangdong Provincial People’s Hospital

    Guangdong, China

    Key Differentiators

    • Cardiology
    • Arrhythmia Detection

Original Source(s)

Self-supervised representation learning reveals explainable physiological structure in high-dimensional magnetocardiography

  • by Dominik D. Kranz, Oruç Kahriman, Dominic Dischl, Sascha Treskatsch, André Sander, Johannes Brachmann, Jai-Wun Park, Niels Wessel

  • June 1, 2026

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