Machine learning-based predictive model for postoperative delirium of elderly patients with coronary heart disease undergoing non-cardiac surgery: a retrospective cohort study - Top-Institutions - MDSpire

Machine learning-based predictive model for postoperative delirium of elderly patients with coronary heart disease undergoing non-cardiac surgery: a retrospective cohort study

  • By

  • Wenjie Kong

  • Jing Jiang

  • Yuanlong Wang

  • Jiayi Chen

  • Bin Wang

  • Kun Wang

  • Yizhi Liang

  • Jiahan Wang

  • Chuan Li

  • Yanan Lin

  • Hongyan Gong

  • Yongxin Liang

  • Yanlin Bi

  • Xu Lin

  • March 27, 2026

  • 0 min

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Top Institutions in Psychiatry

Brief introduction explaining scope and methodology.

  • #1

    Mayo Clinic
    Mayo Clinic

    Rochester, MN

    Key Differentiators

    • Geriatrics
    • Cardiology
    • Anesthesiology
    • Clinical Data Science

  • #2

    Johns Hopkins University
    Johns Hopkins University

    Baltimore, MD

    Key Differentiators

    • Geriatrics
    • Cardiology
    • Anesthesiology
    • Biomedical Informatics

  • #3

    Massachusetts General Hospital
    Massachusetts General Hospital

    Boston, MA

    Key Differentiators

    • Geriatrics
    • Cardiology
    • Anesthesiology
    • Health Data Science

  • #4

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

    San Francisco, CA

    Key Differentiators

    • Geriatrics
    • Cardiology
    • Anesthesiology
    • Clinical Informatics

  • #5

    Cleveland Clinic
    Cleveland Clinic

    Cleveland, OH

    Key Differentiators

    • Cardiology
    • Geriatrics
    • Anesthesiology
    • Data Analytics

Original Source(s)

Machine learning-based predictive model for postoperative delirium of elderly patients with coronary heart disease undergoing non-cardiac surgery: a retrospective cohort study

  • by Wenjie Kong, Jing Jiang, Yuanlong Wang, Jiayi Chen, Bin Wang, Kun Wang, Yizhi Liang, Jiahan Wang, Chuan Li, Yanan Lin, Hongyan Gong, Yongxin Liang, Yanlin Bi, Xu Lin

  • March 27, 2026

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