Assessing artificial intelligence ability in predicting hospitalization duration for pleural empyema patients managed with uniportal video-assisted thoracoscopic surgery: a retrospective observational study.

Journal: BMC surgery
Published Date: May 19, 2025

Abstract

BACKGROUND: This retrospective observational research evaluates the potential applicability of artificial intelligence models to predict the length of hospital stay for patients with pleural empyema who underwent uniportal video-assisted thoracoscopic surgery.

Authors

  • Issa Alnajjar
    Faculty of Medicine, Al-Quds University, Jerusalem, Palestine.
  • Baraa Alshakarnah
    Faculty of Health Science, Al-Quds University, Jerusalem, Palestine.
  • Tasneem AbuShaikha
    Faculty of Medicine, Al-Quds University, Jerusalem, Palestine.
  • Tareq Jarrar
    Faculty of Medicine, Al-Quds University, Jerusalem, Palestine. tareq.jarrar2@students.alquds.edu.
  • Abed Al-Raheem Ozrail
    Faculty of Medicine, Al-Quds University, Jerusalem, Palestine.
  • Yousef Abu Asbeh
    Faculty of Health Science, Al-Quds University, Jerusalem, Palestine. Dryousefabuasbeh@gmail.com.

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