Prediction of delirium occurrence using machine learning in acute stroke patients in intensive care unit.

Journal: Frontiers in neuroscience
Published Date: Jan 9, 2025

Abstract

INTRODUCTION: Delirium, frequently experienced by ischemic stroke patients, is one of the most common neuropsychiatric syndromes reported in the Intensive Care Unit (ICU). Stroke patients with delirium have a high mortality rate and lengthy hospitalization. For these reasons, early diagnosis of delirium in the ICU is critical for better patient prognosis. Therefore, we developed and validated prediction models to classify the real-time delirium status in patients admitted to the ICU or Stroke Unit (SU) with ischemic stroke.

Authors

  • Hyungjun Kim
    Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, Republic of Korea.
  • Min Kim
    Department of Neurology, Ajou University School of Medicine, Suwon, Republic of Korea.
  • Da Young Kim
    Department of Convergence Healthcare Medicine, Graduate School of Ajou University (ALCHeMIST), Suwon, Republic of Korea.
  • Dong Gi Seo
    Department of Biomedical Science, Ajou University Graduate School of Medicine, Suwon, Republic of Korea.
  • Ji Man Hong
    Department of Neurology, Ajou University School of Medicine, Suwon, Republic of Korea.
  • Dukyong Yoon
    Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea.

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