Rapid prediction of cardiac activation in the left ventricle with geometric deep learning: a step towards cardiac resynchronization therapy planning - Top-Institutions - MDSpire

Rapid prediction of cardiac activation in the left ventricle with geometric deep learning: a step towards cardiac resynchronization therapy planning

  • By

  • Ehsan Naghavi

  • Haifeng Wang

  • Vahid Ziaei-Rad

  • Julius Guccione

  • Ghassan Kassab

  • Vishnu Boddeti

  • Seungik Baek

  • Lik-Chuan Lee

  • February 7, 2026

  • 0 min

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Top Institutions in Cardiology

Brief introduction explaining scope and methodology.

  • #1

    Mayo Clinic
    Mayo Clinic

    Rochester, MN

    Key Differentiators

    • Cardiology
    • Cardiac Electrophysiology
    • Biomedical Engineering

  • #2

    Cleveland Clinic
    Cleveland Clinic

    Cleveland, OH

    Key Differentiators

    • Cardiology
    • Cardiac Electrophysiology
    • Biomedical Engineering

  • #3

    Massachusetts General Hospital (MGH)
    Massachusetts General Hospital (MGH)

    Boston, MA

    Key Differentiators

    • Cardiology
    • Cardiac Electrophysiology
    • Biomedical Engineering

  • #4

    Johns Hopkins Hospital
    Johns Hopkins Hospital

    Baltimore, MD

    Key Differentiators

    • Cardiology
    • Cardiac Electrophysiology
    • Biomedical Engineering

  • #5

    Stanford University Medical Center
    Stanford University Medical Center

    Stanford, CA

    Key Differentiators

    • Cardiology
    • Cardiac Electrophysiology
    • Biomedical Engineering

Original Source(s)

Rapid prediction of cardiac activation in the left ventricle with geometric deep learning: a step towards cardiac resynchronization therapy planning

  • by Ehsan Naghavi, Haifeng Wang, Vahid Ziaei-Rad, Julius Guccione, Ghassan Kassab, Vishnu Boddeti, Seungik Baek, Lik-Chuan Lee

  • February 7, 2026

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Publisher Correction: Rapid prediction of cardiac activation in the left ventricle with geometric deep learning: a step towards cardiac resynchronization therapy planning