Machine learning-based prediction of difficult laryngoscopy in infants with Pierre Robin sequence using quantitative 3D computed tomography parameters - Top-Institutions - MDSpire

Machine learning-based prediction of difficult laryngoscopy in infants with Pierre Robin sequence using quantitative 3D computed tomography parameters

  • By

  • Danling Hu

  • Weiwei Cai

  • Anwen Zheng

  • ShuaiLi You

  • Shan Zhong

  • June 24, 2026

  • 0 min

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Top Institutions in Pediatrics

Brief introduction explaining scope and methodology.

  • #1

    Nanjing Children’s Hospital
    Nanjing Children’s Hospital

    Nanjing, Jiangsu

    Key Differentiators

    • Otolaryngology

  • #2

    Nanjing Medical University
    Nanjing Medical University

    Nanjing, Jiangsu

    Key Differentiators

    • Otolaryngology

  • #3

    Dana-Farber Cancer Institute
    Dana-Farber Cancer Institute

    Boston, Massachusetts

    Key Differentiators

    • Otolaryngology

  • #4

    Brigham and Women's Hospital
    Brigham and Women's Hospital

    Boston, Massachusetts

    Key Differentiators

    • Otolaryngology

  • #5

    Mass General Brigham
    Mass General Brigham

    Boston, Massachusetts

    Key Differentiators

    • Otolaryngology

Original Source(s)

Machine learning-based prediction of difficult laryngoscopy in infants with Pierre Robin sequence using quantitative 3D computed tomography parameters

  • by Danling Hu, Weiwei Cai, Anwen Zheng, ShuaiLi You, Shan Zhong

  • June 24, 2026

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