Characterization of clot composition in acute cerebral infarct using machine learning techniques.

Journal: Annals of clinical and translational neurology
Published Date: Apr 1, 2019

Abstract

OBJECTIVE: Clot characteristics can provide information on the cause of cerebral artery occlusion and may guide acute revascularization and secondary prevention strategies. We developed a rapid automated clot analysis system using machine learning (ML) and validated its accuracy in patients undergoing endovascular treatment.

Authors

  • Jong-Won Chung
    Department of Neurology Samsung Medical Center Sungkyunkwan University School of Medicine Seoul Republic of Korea.
  • Yoon-Chul Kim
    Clinical Research Institute Samsung Medical Center Sungkyunkwan University School of Medicine Seoul Republic of Korea.
  • Jihoon Cha
    Department of Radiology Yonsei University Medical Center Yonsei University College of Medicine Seoul Republic of Korea.
  • Eun-Hyeok Choi
    Department of Neurology Samsung Medical Center Sungkyunkwan University School of Medicine Seoul Republic of Korea.
  • Byung Moon Kim
    Department of Radiology Yonsei University Medical Center Yonsei University College of Medicine Seoul Republic of Korea.
  • Woo-Keun Seo
    Department of Neurology Samsung Medical Center Sungkyunkwan University School of Medicine Seoul Republic of Korea.
  • Gyeong-Moon Kim
    Department of Neurology Samsung Medical Center Sungkyunkwan University School of Medicine Seoul Republic of Korea.
  • Oh Young Bang
    Department of Neurology Samsung Medical Center Sungkyunkwan University School of Medicine Seoul Republic of Korea.

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