Expert systems as a diagnostic aid in otoneurology

Area of Science:

• Artificial Intelligence
• Medical Informatics
• Otolaryngology

Background:

• Expert systems (ES) leverage artificial intelligence (AI) for specialized problem-solving.
• ES can emulate human expert behavior and reasoning within specific domains.
• The educational potential of ES lies in their ability to explain conclusions and reasoning processes.

Purpose of the Study:

• To introduce 'Vertigo,' an expert system designed for diagnosing and classifying dizziness.
• To present the development, rationale, structure, and application of the 'Vertigo' ES.
• To highlight the utility of 'Vertigo' as an educational tool in otoneurology.

Main Methods:

• Development of an AI-based expert system named 'Vertigo'.
• Focus on knowledge acquisition and emulation of otoneurological specialists.
• System designed for classification and diagnosis of various dizziness conditions.

Main Results:

• The 'Vertigo' system has been successfully tested on over 200 clinical cases.
• The system demonstrates capability in classifying and diagnosing dizziness.
• Ongoing use by ENT residents in otoneurology training.

Conclusions:

• 'Vertigo' serves as an effective AI-powered educational tool for dizziness diagnosis.
• The expert system facilitates learning and practical application in otoneurology.
• ES like 'Vertigo' can enhance medical education and diagnostic capabilities.