Center of Pressure- and Machine Learning-based Gait Score and Clinical Risk Factors for Predicting Functional Outcome in Acute Ischemic Stroke.

Journal: Archives of physical medicine and rehabilitation
PMID: 39187003

Abstract

OBJECTIVES: To investigate whether machine learning (ML)-based center of pressure (COP) analysis for gait assessment, when used in conjunction with clinical information, offers additive benefits in predicting functional outcomes in patients with acute ischemic stroke.

Authors

  • Eun-Tae Jeon
    Department of Neurology, Korea University Ansan Hospital, Korea University College of Medicine, Ansan, South Korea; Medical Science Research Center, Korea University Ansan Hospital, Korea University College of Medicine, Ansan, South Korea. Electronic address: gksmfskdls@gmail.com.
  • Sang-Hun Lee
    Division of Gynaecologic Oncology, Department of Obstetrics and Gynaecology, University of Ulsan College of Medicine, Ulsan University Hospital, Ulsan, Republic of Korea.
  • Mi-Yeon Eun
    Department of Neurology, Kyungpook National University Chilgok Hospital, School of Medicine, Kyungpook National University, Daegu, South Korea. Electronic address: eunmiyn@gmail.com.
  • Jin-Man Jung
    Department of Neurology, Korea University Ansan Hospital, Korea University College of Medicine, Ansan, South Korea; Korea University Zebrafish Translational Medical Research Center, Ansan, South Korea. Electronic address: sodium1975@korea.ac.kr.

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