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Artificial Intelligence and Pediatric Otolaryngology.

Alice E Huang1, Tulio A Valdez1

  • 1Department of Otolaryngology-Head & Neck Surgery, Stanford University School of Medicine, Stanford, CA, USA.

Otolaryngologic Clinics of North America
|July 20, 2024
PubMed
Summary

Artificial intelligence (AI) enhances pediatric otolaryngology by improving diagnosis and treatment. Machine learning applications are expanding in areas like ear infections, sleep disorders, and surgical procedures.

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Area of Science:

  • Medical Technology
  • Computer Science
  • Pediatric Otolaryngology

Background:

  • Artificial intelligence (AI) simulates human intelligence for data interpretation and decision-making.
  • AI shows growing evidence in diagnosing and triaging pediatric ear infections and sleep disorders.
  • AI is increasingly used for syndromic craniofacial anomalies.

Purpose of the Study:

  • To review the current and emerging applications of AI in pediatric otolaryngology.
  • To highlight AI's role in diagnosis, triaging, and surgical interventions.
  • To discuss the future potential of machine learning in the field.

Main Methods:

  • Review of current literature on AI in pediatric otolaryngology.
  • Analysis of AI applications in diagnosis, triaging, and surgical planning.
Keywords:
Artificial intelligenceChatBotEducation technologyMachine learningNeural networkPatient educationPediatric otolaryngology

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  • Exploration of machine learning in robotic surgery and maxillofacial reconstruction.

    • Main Results:

    • AI is effective in diagnosing and triaging acute otitis media and middle ear effusion.
    • AI aids in the diagnosis of pediatric sleep disorders and syndromic craniofacial anomalies.
    • Machine learning is advancing intraoperative robotic devices and computer-aided surgical planning.

    Conclusions:

    • AI demonstrates significant potential to advance pediatric otolaryngology.
    • Machine learning integration in surgery is a rapidly evolving and promising area.
    • Continued innovation in AI will likely lead to novel applications in otolaryngologic surgery.