Frontiers in Neurology (Dec 2023)

Research on prognostic risk assessment model for acute ischemic stroke based on imaging and multidimensional data

  • Jiabin Liang,
  • Jiabin Liang,
  • Jiabin Liang,
  • Jie Feng,
  • Zhijie Lin,
  • Jinbo Wei,
  • Xun Luo,
  • Qing Mei Wang,
  • Bingjie He,
  • Hanwei Chen,
  • Hanwei Chen,
  • Hanwei Chen,
  • Yufeng Ye,
  • Yufeng Ye

DOI
https://doi.org/10.3389/fneur.2023.1294723
Journal volume & issue
Vol. 14

Abstract

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Accurately assessing the prognostic outcomes of patients with acute ischemic stroke and adjusting treatment plans in a timely manner for those with poor prognosis is crucial for intervening in modifiable risk factors. However, there is still controversy regarding the correlation between imaging-based predictions of complications in acute ischemic stroke. To address this, we developed a cross-modal attention module for integrating multidimensional data, including clinical information, imaging features, treatment plans, prognosis, and complications, to achieve complementary advantages. The fused features preserve magnetic resonance imaging (MRI) characteristics while supplementing clinical relevant information, providing a more comprehensive and informative basis for clinical diagnosis and treatment. The proposed framework based on multidimensional data for activity of daily living (ADL) scoring in patients with acute ischemic stroke demonstrates higher accuracy compared to other state-of-the-art network models, and ablation experiments confirm the effectiveness of each module in the framework.

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