Predicting Popliteal Crease Obliquity Angle Using Machine Learning from Step-Down Kinematics for Early Classification of Osteoarthritis - Top-Institutions - MDSpire

Predicting Popliteal Crease Obliquity Angle Using Machine Learning from Step-Down Kinematics for Early Classification of Osteoarthritis

  • By

  • Ui-Jae Hwang

  • Kyu-sung Chung

  • Siu-ngor Fu

  • Arnold YL Wong

  • Sung-min Ha

  • Il-Kyu Ahn

  • March 1, 2026

  • 0 min

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Top Institutions in Rheumatology

Brief introduction explaining scope and methodology.

  • #1

    Mayo Clinic
    Mayo Clinic

    Rochester, MN

    Key Differentiators

    • Orthopedics
    • Rheumatology
    • Biomedical Engineering
    • Machine Learning

  • #2

    Hospital for Special Surgery (HSS)
    Hospital for Special Surgery (HSS)

    New York, NY

    Key Differentiators

    • Orthopedics
    • Biomechanics
    • Rheumatology

  • #3

    Stanford University School of Medicine
    Stanford University School of Medicine

    Stanford, CA

    Key Differentiators

    • Orthopedics
    • Biomedical Engineering
    • Artificial Intelligence

  • #4

    University of Pittsburgh Medical Center (UPMC)
    University of Pittsburgh Medical Center (UPMC)

    Pittsburgh, PA

    Key Differentiators

    • Orthopedics
    • Rehabilitation Medicine
    • Biomechanics

  • #5

    University of California, San Francisco (UCSF)
    University of California, San Francisco (UCSF)

    San Francisco, CA

    Key Differentiators

    • Rheumatology
    • Orthopedics
    • Biomedical Informatics

Original Source(s)

Predicting Popliteal Crease Obliquity Angle Using Machine Learning from Step-Down Kinematics for Early Classification of Osteoarthritis

  • by Ui-Jae Hwang, Kyu-sung Chung, Siu-ngor Fu, Arnold YL Wong, Sung-min Ha, Il-Kyu Ahn

  • March 1, 2026

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