Journal of Future Medicine and Healthcare Innovation(JFMHI)
ISSN: 3065-7628 | DOI: 10.33140/JFMHI
Raphael Matheus de Souza Makiyama Lopes MD
SANIT (servico de anestesiologia de itajai), Brazil
Publications
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Research Article
Artificial Intelligence-Assisted Monitoring in Anaesthesia: A Systematic Review and Meta-analysis of Diagnostic Accuracy and Clinical Impact AI in Anaesthesia: Monitoring and Outcomes Review
Author(s): Antonio Andrea Camastra MD*, Matheus Requena Escobar MD, Daniel Macedo Oliveira MD, Laiz G. C. Novaes MD, Andre Busatto de Donato MD, Lucas Teixeira Baldo MD, Joao Evangelista Ponte Conrado MD, Cecilia Schettini Gueiros MS, Raphael Matheus de Souza Makiyama Lopes MD and Thomas Rolf Erdmann MD, MsC, PhD
Background: Artificial intelligence (AI) is transforming medicine by enabling real-time data analysis and improved decision-making. In anaesthesiology, AI tools are increasingly used for perioperative risk assessment and intraoperative monitoring, but evidence on their real-world performance and safety remains limited. Methods: We conducted a systematic review and meta-analysis following PRISMA guidelines, including studies from 2010 to May 2025 that evaluated AI applications—machine learning (ML), deep learning, neural networks, and fuzzy logic— in adult patients undergoing general or regional anaesthesia. Primary outcomes were perioperative complications (e.g., hypotension, hypoxia, bradycardia, delirium, vomiting, cardiac arrest, mortality, acute kidney injury [AKI]); secondary outcomes included haemodynamic stability, ICU adm.. Read More»