Impact of Artificial Intelligence on Anesthesia Decision-Making: A Comprehensive Systematic Review - Elang Rizky Ridhoka; Elba Nurdiansyah (International Medical Journal Corp. Ltd, 2025)
Background: Artificial intelligence (AI) integration in anesthesia management offers numerous applications, including predictive models, automated drug delivery, and monitoring of vital signs. However, challenges like ethical considerations and data privacy need to be addressed to ensure AI systems complement human care and patient welfare. Methods: This systematic review adhered to PRISMA 2020 principles and focused exclusively on full-text articles published in English from 2015 to 2025. Editorials and review articles without a DOI were eliminated to preserve the integrity of high-quality sources. A literature review was conducted utilizing esteemed databases like ScienceDirect, PubMed, and SagePub to discover relevant studies. Result: The preliminary database search yielded over 1700 relevant publications on the topic. Following a comprehensive three-stage screening process, eight papers met the specified inclusion criteria and were selected for in-depth analysis. Each study was subjected to a thorough critical assessment, enabling a comprehensive review of the influence of Artificial Intelligence on anesthesia decision-making. This methodical methodology guaranteed that the analysis relied on robust evidence, corresponded with the study's aims, and was capable of producing substantial insights into this intricate relationship. Conclusion: Artificial intelligence is improving clinical anesthesia by enhancing drug delivery precision, risk prediction, and perioperative monitoring. However, challenges like data security, clinician training, and algorithm transparency need to be addressed. Future research should focus on refining AI models, developing standardized guidelines, and fostering seamless integration.