Advances in pediatric perioperative care using artificial intelligence.

Area of Science:

• Pediatric Anesthesia
• Artificial Intelligence in Healthcare
• Perioperative Risk Evaluation

Background:

• AI adoption in healthcare is growing, driven by large datasets from electronic health records.
• Research in pediatric anesthesia, while less extensive than in adults, is advancing, particularly in identifying risk factors for adverse events.
• Current AI tools face challenges in clinical applicability due to a lack of formal external validation and feasibility testing.

Purpose of the Study:

• To explore the application of artificial intelligence (AI) in evaluating risks within pediatric perioperative care.
• To describe potential future uses of AI in pediatric anesthesia, including airway device selection and anesthetic depth management.
• To examine AI's role in training pediatric anesthesia providers.

Main Methods:

• Review of current literature on AI applications in pediatric perioperative care.
• Analysis of AI's potential in risk factor identification for adverse events.
• Exploration of future AI-driven tools for clinical decision support and training.

Main Results:

• AI utilization in healthcare is increasing due to data accessibility.
• Ongoing research focuses on AI for risk factor identification in pediatric anesthesia.
• Uncertainty exists regarding the clinical applicability of current AI tools due to validation gaps.

Conclusions:

• The primary aim of AI in pediatric anesthesia is to support safe and efficient patient care.
• Building confidence among clinicians and families in AI tools is crucial for vulnerable pediatric populations.
• AI holds significant potential to enhance the safety and efficiency of pediatric anesthesia care in the future.