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Emerging artificial intelligence applications in otological imaging.

Gaurav Chawdhary1, Nael Shoman2

  • 1ENT Department, Royal Hallamshire Hospital, Broomhall, Sheffield, UK.

Current Opinion in Otolaryngology & Head and Neck Surgery
|August 30, 2021
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) in otological imaging shows promise for automating tasks like diagnosis and surgical planning. Further research and collaboration are needed to overcome challenges and integrate AI into clinical practice.

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Area of Science:

  • Otolaryngology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Growing demand and workload in healthcare necessitate innovative solutions.
  • Artificial intelligence (AI) is emerging as a transformative technology in medical diagnostics.

Purpose of the Study:

  • To review recent literature on AI applications in otological imaging.
  • To discuss future directions, challenges, and opportunities for AI in this field.

Main Methods:

  • Literature review of recent studies on AI in otological imaging.
  • Analysis of AI applications including automated diagnosis, image segmentation, and biomarker identification.

Main Results:

  • Key AI applications include automated otoscopic image diagnosis and segmentation for surgical simulation.
  • Other studied areas encompass tinnitus MRI biomarkers, facial palsy analysis, and Meniere's disease diagnosis.
  • Current studies are primarily in the preclinical, proof-of-concept stage.

Conclusions:

  • AI in otological imaging holds significant potential for automating healthcare tasks.
  • AI algorithms show comparable or superior performance to physicians in specific areas.
  • Challenges include data acquisition, interdisciplinary collaboration, clinical validation, and building trust.