A machine learning-based predictive model for predicting early neurological deterioration in lenticulostriate atheromatous disease-related infarction.

Journal: Frontiers in neuroscience
Published Date: Dec 11, 2024

Abstract

BACKGROUND AND AIM: This study aimed to develop a predictive model for early neurological deterioration (END) in branch atheromatous disease (BAD) affecting the lenticulostriate artery (LSA) territory using machine learning. Additionally, it aimed to explore the underlying mechanisms of END occurrence in this context.

Authors

  • Zhuangzhuang Jiang
    Department of Neurology, Dongyang People's Hospital, Affiliated to Wenzhou Medical University, Dongyang, China.
  • Dongjuan Xu
    Department of Neurology, Dongyang People's Hospital, Affiliated to Wenzhou Medical University, Dongyang, China.
  • Hongfei Li
    Department of Neurology, Dongyang People's Hospital, Affiliated to Wenzhou Medical University, Dongyang, China.
  • Xiaolan Wu
    Department of Neurology, Dongyang People's Hospital, Affiliated to Wenzhou Medical University, Dongyang, China.
  • Yuan Fang
    Department of Neurology, Dongyang People's Hospital, Affiliated to Wenzhou Medical University, Dongyang, China.
  • Chen Lou
    Department of Neurology, Dongyang People's Hospital, Affiliated to Wenzhou Medical University, Dongyang, China.

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