Performance of multimodal prediction models for intracerebral hemorrhage outcomes using real-world data.

Journal: International journal of medical informatics
Published Date: May 21, 2025

Abstract

BACKGROUND: We aimed to develop and validate multimodal models integrating computed tomography (CT) images, text and tabular clinical data to predict poor functional outcomes and in-hospital mortality in patients with intracerebral hemorrhage (ICH). These models were designed to assist non-specialists in emergency settings with limited access to stroke specialists.

Authors

  • Koutarou Matsumoto
    Saiseikai Kumamoto Hospital, Kumamoto, Japan.
  • Masahiro Suzuki
    Department of Cardiology, Saitama National Hospital, Wako, Japan.
  • Kazuaki Ishihara
    Biostatistics Center Kurume University Kurume Japan.
  • Koki Tokunaga
    Department of Pharmacy Saiseikai Kumamoto Hospital Kumamoto Japan.
  • Katsuhiko Matsuda
    Department of Radiology Saiseikai Kumamoto Hospital Kumamoto Japan.
  • Jenhui Chen
    Artificial Intelligence Research Center, Chang Gung University, Kweishan District, Taoyuan City 33302, Taiwan.
  • Shigeo Yamashiro
    Department of Neurosurgery, Saiseikai Kumamoto Hospital, Stroke Center.
  • Hidehisa Soejima
    Saiseikai Kumamoto Hospital, Kumamoto Japan.
  • Naoki Nakashima
    Medical Information Center, Kyushu University Hospital, Fukuoka, Japan.
  • Masahiro Kamouchi
    Department of Health Care Administration and Management, Graduate School of Medical Sciences Kyushu University Fukuoka Japan.

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