Harnessing machine learning for predicting successful weaning from mechanical ventilation: A systematic review.

Journal: Australian critical care : official journal of the Confederation of Australian Critical Care Nurses
PMID: 40058181

Abstract

BACKGROUND: Machine learning (ML) models represent advanced computational approaches with increasing application in predicting successful weaning from mechanical ventilation (MV). Whilst ML itself has a long history, its application to MV weaning outcomes has emerged more recently. In this systematic review, we assessed the effects of ML on the prediction of successful weaning outcomes amongst adult patients undergoing MV.

Authors

  • Fatma Refaat Ahmed
    Department of Nursing, College of Health Sciences, University of Sharjah, Sharjah, United Arab Emirates; Critical Care and Emergency Nursing Department, Faculty of Nursing, Alexandria University, Alexandria, Egypt. Electronic address: fahmed@sharjah.ac.ae.
  • Nabeel Al-Yateem
    Department of Nursing, College of Health Sciences, University of Sharjah, Sharjah, United Arab Emirates. Electronic address: nalyateem@sharjah.ac.ae.
  • Seyed Aria Nejadghaderi
    HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran; Systematic Review and Meta-analysis Expert Group (SRMEG), Universal Scientific Education and Research Network (USERN), Tehran, Iran. Electronic address: ariang20@gmail.com.
  • Ahmad Rajeh Saifan
    College of Nursing, Yarmouk University, Irbid, Jordan. Electronic address: ahmad.saifan@yu.edu.jo.
  • Sally Mohammed Farghaly Abdelaliem
    Nursing Management and Education Department, College of Nursing, Princess Nourah bint Abdulrahman University, Riyadh, Kingdom of Saudi Arabia; Nursing Administration Department, Faculty of Nursing, Alexandria University, Alexandria, Egypt. Electronic address: sally.farghaly@alexu.edu.eg.
  • Mohannad Eid AbuRuz
    Hind Bint Maktoum College of Nursing and Midwifery, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai Health, Dubai, United Arab Emirates. Electronic address: mohannadeid@yahoo.com.

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