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

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

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. Methods Data from 56 patients w...

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Bibliographic Details
Main Authors:	Issa Alnajjar, Baraa Alshakarnah, Tasneem AbuShaikha, Tareq Jarrar, Abed Al-Raheem Ozrail, Yousef Abu Asbeh
Format:	Article
Language:	English
Published:	BMC 2025-05-01
Series:	BMC Surgery
Subjects:	Artificial Intelligence Machine Learning Length of Stay Pleural Empyema Uniportal Video-Assisted Thoracoscopic Surgery Predictive Modeling
Online Access:	https://doi.org/10.1186/s12893-025-02959-w
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