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Applications of Artificial Intelligence in Neurological Voice Disorders.
Dongren Yao1, Aki Koivu1, Kristina Simonyan1,2
1Department of Otolaryngology-Head and Neck Surgery Massachusetts Eye and Ear and Harvard Medical School Boston Massachusetts USA.
World Journal of Otorhinolaryngology - Head and Neck Surgery
|January 1, 2026
Summary
Artificial intelligence (AI) offers objective voice analysis for neurological voice disorders like Parkinson's disease. AI models show high accuracy in early detection and predicting treatment response, transforming patient care.
Area of Science:
- Neurology
- Speech-Language Pathology
- Computer Science
Background:
- Neurological voice disorders significantly impair communication.
- Traditional diagnosis is subjective; AI offers objective, scalable solutions.
- AI enhances voice analysis for diagnosis, monitoring, and treatment.
Purpose of the Study:
- Review AI applications in neurological voice disorders.
- Examine advancements, challenges, and future of AI-driven voice analysis.
- Evaluate AI effectiveness in detecting and managing these conditions.
Main Methods:
- Analysis of recent literature on AI-based voice analysis.
- Focus on machine learning, deep learning, and signal processing techniques.
- Evaluation of AI model effectiveness using existing studies.
Main Results:
- AI models demonstrate high accuracy in detecting voice impairments.
- AI enables early diagnosis and prediction of treatment response.
- Deep learning methods excel at extracting biomarkers from voice data.
Conclusions:
- AI shows significant potential for early detection and management.
- Challenges include data limitations, privacy, and clinical validation.
- Future research should focus on standardized datasets and model generalizability.
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