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Artificial Intelligence in Rhinology.

Noel F Ayoub¹, Jordan T Glicksman¹

¹Department of Otolaryngology-Head & Neck Surgery, Mass Eye and Ear/Harvard Medical School, Boston, MA, USA.

Otolaryngologic Clinics of North America

|May 31, 2024

Summary

This summary is machine-generated.

Artificial intelligence (AI) offers significant potential to enhance rhinology, allergy, and skull base surgery by improving diagnostics, personalizing medicine, and aiding surgical planning. While many AI models show promise in research, clinical implementation is still developing.

Keywords:

Allergy Artificial intelligence Deep learning Machine learning Natural language processing Rhinology Skull base surgery

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Area of Science:

Otorhinolaryngology
Allergy Immunology
Neurosurgery
Medical Informatics

Background:

Rhinology, allergy, and skull base surgery are complex fields with diverse disease processes.
These specialties present opportunities for artificial intelligence (AI) to improve patient care and enable personalized medicine.
Existing research demonstrates the potential of AI in these areas, though clinical integration is limited.

Purpose of the Study:

To review the current applications and potential of artificial intelligence (AI) in rhinology, allergy, and skull base surgery.
To highlight how AI can augment clinical decision-making and personalize treatment strategies.
To identify key themes in AI research within these surgical and medical subspecialties.

Main Methods:

Review of published research studies on AI in rhinology, allergy, and skull base surgery.
Analysis of AI model development and evaluation, focusing on in silico assessments.
Categorization of AI applications based on their clinical objectives.

Main Results:

AI models are being developed for diagnostic support, clinical decision-making, and patient phenotyping/endotyping.
AI shows potential in predicting treatment outcomes and assisting with surgical planning.
Most current AI studies focus on in silico evaluations rather than direct clinical implementation.

Conclusions:

Artificial intelligence holds considerable promise for advancing rhinology, allergy, and skull base surgery.
AI can enhance diagnostic accuracy, personalize treatment, and optimize surgical interventions.
Further research and clinical validation are needed to fully realize the benefits of AI in these fields.