Screening prediction models using artificial intelligence for moderate-to-severe obstructive sleep apnea in patients with acute ischemic stroke.

Journal: Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
PMID: 39722420

Abstract

BACKGROUND: Obstructive sleep apnea (OSA) is common after stroke. Still, routine screening of OSA with polysomnography (PSG) is often unfeasible in clinical practice, primarily because of how limited resources are and the physical condition of patients. In this study, we used several artificial intelligence techniques to predict moderate-to-severe OSA and identify its features in patients with acute ischemic stroke.

Authors

  • Huan-Jan Lin
    Doctoral Degree Program in Biomedical Engineering, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan; Department of Neurology, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan; Post Baccalaureate Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan.
  • Tian-Hsiang Huang
    Center for Big Data Research, Kaohsiung Medical University, No. 100, Shin-Chuan 1st Road, Kaohsiung, 807, Taiwan.
  • Hui-Ci Huang
    Department of Healthcare Administration and Medical Informatics, Kaohsiung Medical University, Kaohsiung, Taiwan.
  • Pao-Li Hsiao
    Department of Neurology, E-DA Hospital, Kaohsiung, Taiwan.
  • Wen-Hsien Ho
    Department of Healthcare Administration and Medical Informatics, 38023Kaohsiung Medical University, Kaohsiung 807, Taiwan.

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