Development and validation of an explainable machine learning prediction model of hemorrhagic transformation after intravenous thrombolysis in stroke.

Journal: Frontiers in neurology
Published Date: Jan 15, 2025

Abstract

OBJECTIVE: To develop and validate an explainable machine learning (ML) model predicting the risk of hemorrhagic transformation (HT) after intravenous thrombolysis.

Authors

  • Yanan Lin
    Department of Neurology, The First Affiliated Hospital of Dalian Medical University, Dalian, China.
  • Yan Li
    Interdisciplinary Research Center for Biology and Chemistry, Liaoning Normal University, Dalian, China.
  • Yayin Luo
    Department of Neurology, The First Affiliated Hospital of Dalian Medical University, Dalian, China.
  • Jie Han
    Department of Neurology, The First Affiliated Hospital of Dalian Medical University, Dalian, China.

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