Deep learning-based personalised outcome prediction after acute ischaemic stroke.

Journal: Journal of neurology, neurosurgery, and psychiatry
Published Date: Jan 17, 2023

Abstract

BACKGROUND: Whether deep learning models using clinical data and brain imaging can predict the long-term risk of major adverse cerebro/cardiovascular events (MACE) after acute ischaemic stroke (AIS) at the individual level has not yet been studied.

Authors

  • Doo-Young Kim
    Department of Artificial Intelligence Convergence, Chonnam National University, Gwangju, Korea (the Republic of).
  • Kang-Ho Choi
    Department of Neurology, Chonnam National University Medical School and Hospital, Gwangju, Korea (the Republic of) jhbt0607@hanmail.net ckhchoikang@hanmail.net.
  • Ja-Hae Kim
    Department of Artificial Intelligence Convergence, Chonnam National University, Gwangju, Korea (the Republic of) jhbt0607@hanmail.net ckhchoikang@hanmail.net.
  • Jina Hong
    Department of Biomedical Sciences, Chonnam National University, Gwangju, Korea (the Republic of).
  • Seong-Min Choi
    Department of Neurology, Chonnam National University Medical School and Hospital, Gwangju, Korea (the Republic of).
  • Man-Seok Park
    Department of Neurology, Chonnam National University Medical School and Hospital, Gwangju, Korea (the Republic of).
  • Ki-Hyun Cho
    Department of Neurology, Chonnam National University Medical School and Hospital, Gwangju, Korea (the Republic of).

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