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Updated: May 10, 2025

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In Vivo Morphometric Analysis of Human Cranial Nerves Using Magnetic Resonance Imaging in Menière's Disease Ears and Normal Hearing Ears
Published on: February 21, 2018
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[Artificial intelligence applications in Ménière's disease]
Ziyi Zhou1, Yiling Zhang1, Qiuyue Mao1
1Department of Otolaryngology Head and Neck Surgery,the Second Xiangya Hospital,Central South University,Changsha,410011,China.
Summary
Artificial intelligence (AI) offers promising solutions for diagnosing and managing Ménière
Area of Science:
- Otolaryngology and Medical Informatics
- Application of Artificial Intelligence in Healthcare
Background:
- Ménière's disease (MD) presents diagnostic challenges due to fluctuating symptoms and lack of definitive diagnostic criteria.
- Accurate diagnosis and management of MD are crucial for patient well-being and preventing disease progression.
Purpose of the Study:
- To review the current and potential applications of artificial intelligence (AI) in the diagnosis and management of Ménière's disease.
- To explore AI's role in differentiating MD from other vertigo causes, evaluating Endolymphatic Hydrops (EH), and predicting disease progression.
Main Methods:
- Review of existing literature on AI applications in Ménière's disease.
- Analysis of AI's utility in interpreting imaging and biochemical data related to Endolymphatic Hydrops (EH).
- Examination of AI algorithms for clinical decision support in MD patient management.
Main Results:
- AI demonstrates potential in distinguishing MD from other vertigo etiologies.
- AI can aid in the assessment of Endolymphatic Hydrops (EH) through advanced data analysis.
- AI tools show promise in managing MD patients and forecasting disease trajectory.
Conclusions:
- Artificial intelligence presents a significant opportunity to improve Ménière's disease diagnosis and patient care.
- Overcoming challenges in clinical integration is key to realizing AI's full potential in MD management.
- Future research should focus on validating AI tools and addressing implementation barriers.

