Predicting SIRS after PCNL using machine learning: the joint impact of sarcopenia and staghorn stones - Top-Institutions - MDSpire

Predicting SIRS after PCNL using machine learning: the joint impact of sarcopenia and staghorn stones

  • By

  • Song Wei

  • Boran Lv

  • Baiyu Liu

  • Qunxiong Huang

  • Cheng Hu

  • Hua Wang

  • June 25, 2026

  • 0 min

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Top Institutions in Infectious Disease

Brief introduction explaining scope and methodology.

  • #1

    Third Affiliated Hospital of Sun Yat-sen University
    Third Affiliated Hospital of Sun Yat-sen University

    Guangzhou, Guangdong

    Key Differentiators

    • Urology

  • #2

    Wuhan Union Hospital
    Wuhan Union Hospital

    Wuhan, Hubei

    Key Differentiators

    • Urology

  • #3

    single tertiary-referral academic center
    single tertiary-referral academic center

    Unknown, Unknown

    Key Differentiators

    • Urology

Original Source(s)

Predicting SIRS after PCNL using machine learning: the joint impact of sarcopenia and staghorn stones

  • by Song Wei, Boran Lv, Baiyu Liu, Qunxiong Huang, Cheng Hu, Hua Wang

  • June 25, 2026

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