Machine learning for predicting hematoma expansion in spontaneous intracerebral hemorrhage: a systematic review and meta-analysis.

Journal: Neuroradiology
Published Date:

Abstract

PURPOSE: Early identification of hematoma enlargement and persistent hematoma expansion (HE) in patients with cerebral hemorrhage is increasingly crucial for determining clinical treatments. However, due to the lack of clinically effective tools, radiomics has been gradually introduced into the early identification of hematoma enlargement. Though, radiomics has limited predictive accuracy due to variations in procedures. Therefore, we conducted a systematic review and meta-analysis to explore the value of radiomics in the early detection of HE in patients with cerebral hemorrhage.

Authors

  • Yihua Liu
    Department of General medical subjects, Ezhou Central Hospital, Ezhou Hubei, 436000, China.
  • Fengfeng Zhao
    School of Clinical Medicine, Weifang Medical University, Weifang, 261000, China.
  • Enjing Niu
    Department of Adult Internal Medicine, Qingdao Women's and Children's Hospital, No. 217 Liaoyang West Street, Shibei District, Qingdao, 266000, Shandong, China.
  • Liang Chen
    Department of Neurosurgery, Huashan Hospital, Fudan University, Shanghai, China.