Predicting post-surgical functional status in high-grade glioma with resting state fMRI and machine learning - Top-Institutions - MDSpire

Predicting post-surgical functional status in high-grade glioma with resting state fMRI and machine learning

  • By

  • Patrick H. Luckett

  • Michael O. Olufawo

  • Ki Yun Park

  • Bidhan Lamichhane

  • Donna Dierker

  • Gabriel Trevino Verastegui

  • John J. Lee

  • Peter Yang

  • Albert Kim

  • Omar H. Butt

  • Milan G. Chheda

  • Abraham Z. Snyder

  • Joshua S. Shimony

  • Eric C. Leuthardt

  • May 24, 2024

  • 0 min

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Top Institutions in Oncology

Brief introduction explaining scope and methodology.

  • #1

    Massachusetts General Hospital
    Massachusetts General Hospital

    Boston, MA

    Key Differentiators

    • Neuro-oncology
    • Neurosurgery
    • Neuroimaging
    • Machine Learning

  • #2

    Johns Hopkins Hospital
    Johns Hopkins Hospital

    Baltimore, MD

    Key Differentiators

    • Neuro-oncology
    • Neurosurgery
    • Neuroimaging

  • #3

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

    San Francisco, CA

    Key Differentiators

    • Neuro-oncology
    • Neurosurgery
    • Neuroimaging
    • Biomedical Informatics

  • #4

    Memorial Sloan Kettering Cancer Center
    Memorial Sloan Kettering Cancer Center

    New York, NY

    Key Differentiators

    • Neuro-oncology
    • Radiology
    • Neurosurgery

Original Source(s)

Predicting post-surgical functional status in high-grade glioma with resting state fMRI and machine learning

  • by Patrick H. Luckett, Michael O. Olufawo, Ki Yun Park, Bidhan Lamichhane, Donna Dierker, Gabriel Trevino Verastegui, John J. Lee, Peter Yang, Albert Kim, Omar H. Butt, Milan G. Chheda, Abraham Z. Snyder, Joshua S. Shimony, Eric C. Leuthardt

  • May 24, 2024

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