AI-driven cardiovascular risk prediction in patients with diabetes: bridging algorithmic innovation to equitable clinical application - Top-Institutions - MDSpire

AI-driven cardiovascular risk prediction in patients with diabetes: bridging algorithmic innovation to equitable clinical application

  • By

  • Hongxuan Li

  • Zheyi Xu

  • Yanhui Cen

  • Xin Liu

  • June 2, 2026

  • 0 min

Share

Top Institutions in Cardiology

Brief introduction explaining scope and methodology.

  • #1

    Mayo Clinic
    Mayo Clinic

    Rochester, Minnesota

    Key Differentiators

    • Cardiology

  • #2

    Cedars-Sinai Medical Center, Smidt Heart Institute
    Cedars-Sinai Medical Center, Smidt Heart Institute

    Los Angeles, California

    Key Differentiators

    • Cardiology

  • #3

    National Heart and Lung Institute, Imperial College London
    National Heart and Lung Institute, Imperial College London

    London, England

    Key Differentiators

    • Cardiology

  • #4

    Royal Brompton and Harefield Hospitals
    Royal Brompton and Harefield Hospitals

    London, England

    Key Differentiators

    • Cardiology

  • #5

    University of Zurich
    University of Zurich

    Zurich, Switzerland

    Key Differentiators

    • Cardiology

Original Source(s)

AI-driven cardiovascular risk prediction in patients with diabetes: bridging algorithmic innovation to equitable clinical application

  • by Hongxuan Li, Zheyi Xu, Yanhui Cen, Xin Liu

  • June 2, 2026

Related Content

Neo or Not Neo? Widefield OCT-A Reveals Hidden Neovascularization

Utilizing OCT and OCT-A technologies revealed critical insights into a patient’s complex retinopathy, as highlighted by Dr. Julie Rodman.

Gov. Patrick Morrisey walking Mountaineer Miles to encourage West Virginians to lose weight

Sharper Imaging, Smarter Tools: Inside the MonacoPro

With its combination of UWF imaging, OCT integration, and intelligent review tools, the MonacoPro represents the next step in comprehensive retinal evaluation. By improving image quality, enhancing diagnostic confidence, and streamlining workflow, the system supports clinicians in delivering more efficient, informed, and patient-centered care.