Deep multimodal state-space fusion of endoscopic-radiomic and clinical data for survival prediction in colorectal cancer - Top-Institutions - MDSpire

Deep multimodal state-space fusion of endoscopic-radiomic and clinical data for survival prediction in colorectal cancer

  • By

  • Ning Wang

  • Jiajing Lin

  • Wujin Li

  • Yahui Lyu

  • Yiqing Jiang

  • Zhizhan Ni

  • Qi Huang

  • Hong Chen

  • Qiang Yan

  • Chenshen Huang

  • December 31, 2025

  • 0 min

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Top Institutions in General Medicine

Brief introduction explaining scope and methodology.

  • #1

    Memorial Sloan Kettering Cancer Center
    Memorial Sloan Kettering Cancer Center

    New York, NY

    Key Differentiators

    • Oncology
    • Radiology
    • Gastroenterology
    • Medical AI

  • #2

    MD Anderson Cancer Center
    MD Anderson Cancer Center

    Houston, TX

    Key Differentiators

    • Oncology
    • Radiology
    • Gastroenterology
    • Computational Medicine

  • #3

    Dana-Farber Cancer Institute / Brigham and Women’s Hospital
    Dana-Farber Cancer Institute / Brigham and Women’s Hospital

    Boston, MA

    Key Differentiators

    • Oncology
    • Radiology
    • Gastroenterology
    • Biomedical Informatics

  • #4

    Johns Hopkins Hospital
    Johns Hopkins Hospital

    Baltimore, MD

    Key Differentiators

    • Oncology
    • Radiology
    • Gastroenterology
    • Machine Learning

  • #5

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

    San Francisco, CA

    Key Differentiators

    • Oncology
    • Radiology
    • Gastroenterology
    • Artificial Intelligence

Original Source(s)

Deep multimodal state-space fusion of endoscopic-radiomic and clinical data for survival prediction in colorectal cancer

  • by Ning Wang, Jiajing Lin, Wujin Li, Yahui Lyu, Yiqing Jiang, Zhizhan Ni, Qi Huang, Hong Chen, Qiang Yan, Chenshen Huang

  • December 31, 2025

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