Classification of laryngeal diseases including laryngeal cancer, benign mucosal disease, and vocal cord paralysis by artificial intelligence using voice analysisopen access
- Authors
- Kim, Hyun-Bum; Song, Jaemin; Park, Seho; Lee, Yong Oh
- Issue Date
- Apr-2024
- Publisher
- Nature Research
- Keywords
- Artificial intelligence; Laryngeal neoplasm; Vocal paralysis; Voice; Voice change
- Citation
- Scientific Reports, v.14, no.1
- Journal Title
- Scientific Reports
- Volume
- 14
- Number
- 1
- URI
- https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/33193
- DOI
- 10.1038/s41598-024-58817-x
- ISSN
- 2045-2322
- Abstract
- Voice change is often the first sign of laryngeal cancer, leading to diagnosis through hospital laryngoscopy. Screening for laryngeal cancer solely based on voice could enhance early detection. However, identifying voice indicators specific to laryngeal cancer is challenging, especially when differentiating it from other laryngeal ailments. This study presents an artificial intelligence model designed to distinguish between healthy voices, laryngeal cancer voices, and those of the other laryngeal conditions. We gathered voice samples of individuals with laryngeal cancer, vocal cord paralysis, benign mucosal diseases, and healthy participants. Comprehensive testing was conducted to determine the best mel-frequency cepstral coefficient conversion and machine learning techniques, with results analyzed in-depth. In our tests, laryngeal diseases distinguishing from healthy voices achieved an accuracy of 0.85–0.97. However, when multiclass classification, accuracy ranged from 0.75 to 0.83. These findings highlight the challenges of artificial intelligence-driven voice-based diagnosis due to overlaps with benign conditions but also underscore its potential. © The Author(s) 2024.
- Files in This Item
- There are no files associated with this item.
- Appears in
Collections - ETC > 1. Journal Articles
![qrcode](https://api.qrserver.com/v1/create-qr-code/?size=55x55&data=https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/33193)
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.