Prediction of early neurological deterioration in acute minor ischemic stroke by machine learning algorithms.

Journal: Clinical neurology and neurosurgery
Published Date: May 5, 2020

Abstract

OBJECTIVES: A significant proportion of patients with acute minor stroke have unfavorable functional outcome due to early neurological deterioration (END). The purpose of this study was to evaluate the applicability of machine learning algorithms to predict END in patients with acute minor stroke.

Authors

  • Sang Min Sung
    Stroke Center, Pusan National University Hospital, School of Medicine, Busan, Republic of Korea; Department of Neurology, Pusan National University Hospital, School of Medicine, Busan, Republic of Korea; Biomedical Research Institute, Pusan National University Hospital, School of Medicine, Busan, Republic of Korea. Electronic address: aminoff@hanmail.net.
  • Yoon Jung Kang
    Stroke Center, Pusan National University Hospital, School of Medicine, Busan, Republic of Korea; Department of Neurology, Pusan National University Hospital, School of Medicine, Busan, Republic of Korea.
  • Han Jin Cho
    Stroke Center, Pusan National University Hospital, School of Medicine, Busan, Republic of Korea; Department of Neurology, Pusan National University Hospital, School of Medicine, Busan, Republic of Korea.
  • Nae Ri Kim
    Stroke Center, Pusan National University Hospital, School of Medicine, Busan, Republic of Korea; Department of Neurology, Pusan National University Hospital, School of Medicine, Busan, Republic of Korea.
  • Suk Min Lee
    c Department of Physical Therapy , Sahmyook University , Seoul , Republic of Korea.
  • Byung Kwan Choi
    Stroke Center, Pusan National University Hospital, School of Medicine, Busan, Republic of Korea; Department of Neurosurgery, Pusan National University Hospital, School of Medicine, Busan, Republic of Korea.
  • Giphil Cho
    Finance Fishery Manufacture Industrial Mathematics Center on Big Data, Pusan National University, Busan, Republic of Korea.

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