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The human larynx, often referred to as the voice box, is an intricate organ located in the neck. It serves as a pathway for air to enter the lungs during respiration and is an essential component of voice production.
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AI-Powered Laryngoscopy: Exploring the Future With Google Gemini.

Sean A Setzen1, Katerina Andreadis2, Olivier Elemento3

  • 1Sean Parker Institute for the Voice, Department of Otolaryngology-Head and Neck Surgery, Weill Cornell Medical College, New York, New York, USA.

The Laryngoscope
|February 20, 2025
PubMed
Summary

Google Gemini 1.5 Pro, a powerful AI foundation model (FM), shows promise in interpreting laryngoscopy images and videos. This AI tool could aid otolaryngology by supporting clinical decisions in complex procedures.

Keywords:
Google Geminiartificial intelligencefoundational modelslaryngologymachine learning

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Area of Science:

  • Artificial Intelligence in Medicine
  • Otolaryngology
  • Medical Imaging Analysis

Background:

  • Foundation models (FMs) are versatile AI systems trained on diverse data.
  • Multimodal FMs can process various data types, including video.
  • AI's role in clinical decision support is rapidly expanding.

Purpose of the Study:

  • To evaluate Google Gemini 1.5 Pro's performance in interpreting laryngoscopy images and videos.
  • To assess the potential of advanced foundation models in otolaryngology.

Main Methods:

  • Google Gemini 1.5 Pro was used to analyze laryngoscopy frames and videos from Google Images and YouTube.
  • The model's ability to recognize the procedure, diagnose pathology, and identify lesion sides was tested.
  • Performance was evaluated without specific fine-tuning for the task.

Main Results:

  • Gemini 1.5 Pro recognized laryngoscopy in 98.9% of frames and 100% of videos.
  • Accurate pathology diagnosis was achieved in 62.5% of frames and 20.0% of videos.
  • The model identified lesion sides in 65.9% of frames and 40.0% of videos, and narrated operative videos.

Conclusions:

  • Google Gemini 1.5 Pro demonstrates significant potential for analyzing laryngoscopy procedures.
  • Foundation models show promise as clinical decision support tools in specialized medical fields like otolaryngology.