Why the study?
AI has seen limited focus in pediatric anesthesia compared to adult anesthesia, and uncertainty persists surrounding the clinical applicability of existing tools due to lack of formal external validation or feasibility testing.
Artificial intelligence shows potential for improving risk evaluation and clinical decision-making in pediatric perioperative care, but requires further external validation before widespread clinical application.
Should not yet change pediatric anesthesia practice; leaves open need for external validation of AI tools.
PURPOSE OF THIS REVIEW: This article explores how artificial intelligence (AI) can be used to evaluate risks in pediatric perioperative care. It will also describe potential future applications of AI, such as models for airway device selection, controlling anesthetic depth and nociception during surgery, and contributing to the training of pediatric anesthesia providers. RECENT FINDINGS: The use of AI in healthcare has increased in recent years, largely due to the accessibility of large datasets, such as those gathered from electronic health records. Although there has been less focus on pediatric anesthesia compared to adult anesthesia, research is on- going, especially for applications focused on risk factor identification for adverse perioperative events. Despite these advances, the lack of formal external validation or feasibility testing results in uncertainty surrounding the clinical applicability of these tools. SUMMARY: The goal of using AI in pediatric anesthesia is to assist clinicians in providing safe and efficient care. Given that children are a vulnerable population, it is crucial to ensure that both clinicians and families have confidence in the clinical tools used to inform medical decision- making. While not yet a reality, the eventual incorporation of AI-based tools holds great potential to contribute to the safe and efficient care of our patients.
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Dundaru-Bandi et al. (2024) studied this question.
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