Evaluating Radiomics, Deep Learning, and Hybrid Models for Forecasting Hidden Pleural Spread in Non-Small Cell Lung Cancer Patients: A Retrospective Multicenter Analysis - Top-Institutions - MDSpire

Evaluating Radiomics, Deep Learning, and Hybrid Models for Forecasting Hidden Pleural Spread in Non-Small Cell Lung Cancer Patients: A Retrospective Multicenter Analysis

  • By

  • Tao Bao

  • Xiaoguang Li

  • Yuanlin Deng

  • Liang Chen

  • Weijie Sun

  • Mingjian Ge

  • Jigang Dai

  • Xiaolong Zhao

  • Xu Chen

  • Liang Zhang

  • Lei Bao

  • Wei Guo

  • October 29, 2025

  • 0 min

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Top Institutions in Pulmonary

Brief introduction explaining scope and methodology.

  • #1

    Memorial Sloan Kettering Cancer Center
    Memorial Sloan Kettering Cancer Center

    New York, NY

    Key Differentiators

    • Thoracic Oncology
    • Radiology
    • Medical Imaging Informatics
    • Machine Learning in Oncology

  • #2

    MD Anderson Cancer Center
    MD Anderson Cancer Center

    Houston, TX

    Key Differentiators

    • Thoracic Oncology
    • Radiology
    • Artificial Intelligence in Medicine

  • #3

    Massachusetts General Hospital / Harvard Medical School
    Massachusetts General Hospital / Harvard Medical School

    Boston, MA

    Key Differentiators

    • Thoracic Surgery
    • Radiology
    • Biomedical Imaging
    • Machine Learning

  • #4

    National Cancer Center Hospital
    National Cancer Center Hospital

    Tokyo, Tokyo Prefecture

    Key Differentiators

    • Thoracic Oncology
    • Radiology
    • Medical AI Research

  • #5

    Fudan University Shanghai Cancer Center
    Fudan University Shanghai Cancer Center

    Shanghai, Shanghai

    Key Differentiators

    • Thoracic Oncology
    • Radiology
    • Radiomics
    • Deep Learning

Original Source(s)

Evaluating Radiomics, Deep Learning, and Hybrid Models for Forecasting Hidden Pleural Spread in Non-Small Cell Lung Cancer Patients: A Retrospective Multicenter Analysis

  • by Tao Bao, Xiaoguang Li, Yuanlin Deng, Liang Chen, Weijie Sun, Mingjian Ge, Jigang Dai, Xiaolong Zhao, Xu Chen, Liang Zhang, Lei Bao, Wei Guo

  • October 29, 2025

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