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Using artificial intelligence to advance pediatric infection prevention and control.

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Artificial intelligence (AI) can aid infection prevention and control (IP&C) in communities and hospitals. However, more research is needed on AI

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Area of Science:

  • Infection Prevention and Control
  • Artificial Intelligence Applications
  • Pediatric Healthcare

Background:

  • Artificial intelligence (AI) shows promise for infection prevention and control (IP&C).
  • Most current AI applications in IP&C focus on adult populations.
  • Pediatric populations require specific considerations for AI implementation in IP&C.

Purpose of the Study:

  • To review the potential of AI in enhancing IP&C for pediatric populations.
  • To identify current applications and limitations of AI in pediatric IP&C.
  • To explore AI's role in both community and healthcare settings for children.

Main Methods:

  • Literature review of AI applications in infection prevention and control.
  • Exploration of AI's utility in community and healthcare settings for pediatric populations.
  • Analysis of existing data and identification of limitations.

Main Results:

  • AI can educate families, detect outbreaks, and prescreen patients in the community.
  • AI assists in identifying at-risk patients for healthcare-associated infections (HAIs) and surveillance.
  • Limitations include data bias and a lack of prospective validation studies in diverse pediatric groups.

Conclusions:

  • AI offers significant potential as a tool for infection recognition and control in pediatric settings.
  • Further prospective studies are essential to validate AI tools developed for pediatric IP&C.
  • Addressing data biases and heterogeneity in pediatric populations is crucial for effective AI deployment.