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Machine learning based identification of relevant parameters for functional voice disorders derived from endoscopic high-speed recordings
In voice research and clinical assessment, many objective parameters are in use. However, there is no commonly used set of parameters that reflect certain voice disorders, such as functional dysphonia (FD); i.e. disorders with no visible anatomical changes. Hence, 358 high-speed videoendoscopy (HSV)...
Salvato in:
| Pubblicato in: | Sci Rep |
|---|---|
| Autori principali: | , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Nature Publishing Group UK
2020
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7324600/ https://ncbi.nlm.nih.gov/pubmed/32601277 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-020-66405-y |
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