Diffusion-Weighted Imaging-Based Radiomics Features and Machine Learning Method to Predict the 90-Day Prognosis in Patients With Acute Ischemic Stroke.

Journal: The neurologist
PMID: 40035203

Abstract

OBJECTIVES: The evaluation of the prognosis of patients with acute ischemic stroke (AIS) is of great significance in clinical practice. We aim to evaluate the feasibility and effectiveness of diffusion-weighted imaging (DWI) image-based radiomics features and machine learning methods in predicting 90-day prognosis among patients with AIS.

Authors

  • Guirui Li
    Department of Neurology, The Second Affiliated Hospital of Guangxi Medical University, Nanning.
  • Yueling Zhang
    The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China. Electronic address: 89263084@qq.com.
  • Jian Tang
    Department of Decision Sciences HEC, Université de Montréal, Montreal, Québec, Canada.
  • Shijian Chen
    Department of Neurology, The Fourth Affiliated Hospital of Guangxi Medical University, Liuzhou, Guangxi, China.
  • Qianqian Liu
    The First Clinical Medical College, Lanzhou University, Lanzhou, China.
  • Jian Zhang
    College of Pharmacy, Ningxia Medical University, Yinchuan, NingxiaHui Autonomous Region, China.
  • Shengliang Shi
    The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China. Electronic address: ssl_1964@163.com.

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