Machine Learning in Assessing Intraoperative Blood Loss: A Systematic Review and Meta-Analysis.

Key Points

• This research aims to evaluate the effectiveness of machine learning in assessing intraoperative blood loss.
• Conducted a systematic review of existing literature on machine learning applications in intraoperative blood loss assessment.
• Performed a meta-analysis to synthesize findings from multiple studies on the topic.
• Explored implications for interdisciplinary approaches in nursing.
• Identified several studies demonstrating favorable outcomes of machine learning for intraoperative blood loss assessment.
• Showed that machine learning models can improve accuracy in predicting blood loss during surgeries.
• Highlighted the potential for machine learning to enhance innovation in nursing practices.