Machine learning prediction model for functional prognosis of acute ischemic stroke based on MRI radiomics of white matter hyperintensities.

Journal: BMC medical imaging
PMID: 40108506

Abstract

OBJECTIVE: The purpose of the current study is to explore the value of a nomogram that integrates clinical factors and MRI white matter hyperintensities (WMH) radiomics features in predicting the prognosis at 90 days for patients with acute ischemic stroke (AIS).

Authors

  • Yayuan Xia
    The Affiliated Xuzhou Clinical College of Xuzhou Medical University, Xuzhou, 221009, China.
  • Linhui Li
    College of Artificial Intelligence, China University of Petroleum Beijing (CUPB), Beijing 102249, PR China.
  • Peipei Liu
    Department of Radiology, Xuzhou Central Hospital, No. 199, Jiefang South Road, Quanshan District, Xuzhou City, Jiangsu Province, 221009, PR China.
  • Tianxu Zhai
    Department of Radiology, Nanyang First People's Hospital, Nanyang, 473000, China.
  • Yibing Shi
    From the Department of Radiology, Xuzhou Central Hospital, Xuzhou, China.

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