Evaluation of large language models for diagnostic impression generation from brain MRI report findings: a multicenter benchmark and reader study - Top-Institutions - MDSpire

Evaluation of large language models for diagnostic impression generation from brain MRI report findings: a multicenter benchmark and reader study

  • By

  • Ming-Liang Wang

  • Rui-Peng Zhang

  • Wen-Juan Wu

  • Yu Lu

  • Xiao-Er Wei

  • Zheng Sun

  • Bao-Hui Guan

  • Jun-Jie Zhang

  • Xue Wu

  • Lei Zhang

  • Tian-Le Wang

  • Yue-Hua Li

  • January 22, 2026

  • 0 min

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Top Institutions in Radiology

Brief introduction explaining scope and methodology.

  • #1

    Massachusetts General Hospital
    Massachusetts General Hospital

    Boston, MA

    Key Differentiators

    • Radiology
    • Neuroradiology
    • Medical Imaging Informatics
    • Artificial Intelligence in Medicine

  • #2

    Stanford University Medical Center
    Stanford University Medical Center

    Stanford, CA

    Key Differentiators

    • Radiology
    • Neuroradiology
    • Biomedical Informatics
    • Machine Learning

  • #3

    Johns Hopkins Hospital
    Johns Hopkins Hospital

    Baltimore, MD

    Key Differentiators

    • Radiology
    • Neuroradiology
    • Clinical Neuroscience
    • Health Informatics

  • #4

    Mayo Clinic
    Mayo Clinic

    Rochester, MN

    Key Differentiators

    • Radiology
    • Neuroradiology
    • Medical Informatics
    • AI in Healthcare

  • #5

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

    San Francisco, CA

    Key Differentiators

    • Radiology
    • Neuroradiology
    • Biomedical Imaging
    • AI Research

Original Source(s)

Evaluation of large language models for diagnostic impression generation from brain MRI report findings: a multicenter benchmark and reader study

  • by Ming-Liang Wang, Rui-Peng Zhang, Wen-Juan Wu, Yu Lu, Xiao-Er Wei, Zheng Sun, Bao-Hui Guan, Jun-Jie Zhang, Xue Wu, Lei Zhang, Tian-Le Wang, Yue-Hua Li

  • January 22, 2026

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