Forecasting Surgical Duration in Pediatric Urology Using a Deep Learning Model That Integrates Multimodal Patient and Physician Data - Top-Institutions - MDSpire

Forecasting Surgical Duration in Pediatric Urology Using a Deep Learning Model That Integrates Multimodal Patient and Physician Data

  • By

  • Yonggen Zhao

  • Ruoge Lin

  • Yiying Sun

  • Lingdong Chen

  • Jian Huang

  • Guangjie Chen

  • Zhu Zhu

  • Gang Yu

  • April 28, 2026

  • 0 min

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Top Institutions in Urology

Brief introduction explaining scope and methodology.

  • #1

    Boston Children's Hospital
    Boston Children's Hospital

    Boston, MA

    Key Differentiators

    • Pediatric Urology
    • Surgical Informatics
    • Machine Learning in Healthcare

  • #2

    Cincinnati Children's Hospital Medical Center
    Cincinnati Children's Hospital Medical Center

    Cincinnati, OH

    Key Differentiators

    • Pediatric Urology
    • Clinical Data Science
    • Perioperative Analytics

  • #3

    Children's Hospital of Philadelphia (CHOP)
    Children's Hospital of Philadelphia (CHOP)

    Philadelphia, PA

    Key Differentiators

    • Pediatric Urology
    • Biomedical Informatics
    • Surgical Outcomes Research

  • #4

    Stanford University School of Medicine
    Stanford University School of Medicine

    Stanford, CA

    Key Differentiators

    • Urology
    • Artificial Intelligence in Medicine
    • Surgical Data Science

  • #5

    Johns Hopkins Hospital
    Johns Hopkins Hospital

    Baltimore, MD

    Key Differentiators

    • Urology
    • Health Informatics
    • Perioperative Management

Original Source(s)

Forecasting Surgical Duration in Pediatric Urology Using a Deep Learning Model That Integrates Multimodal Patient and Physician Data

  • by Yonggen Zhao, Ruoge Lin, Yiying Sun, Lingdong Chen, Jian Huang, Guangjie Chen, Zhu Zhu, Gang Yu

  • April 28, 2026

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