Modeling the Progression of Speech Deficits in Cerebellar Ataxia Using a Mixture Mixed-Effect Machine Learning Framework

Modeling the Progression of Speech Deficits in Cerebellar Ataxia Using a Mixture Mixed-Effect Machine Learning Framework

Background: Accurate and reliable prediction of changes in the severity of cerebellar ataxia (CA) will be necessary for trials of disease-modifying therapies. Cerebellar dysarthria (CD) is a common feature of CA. This study demonstrated that objective acoustic measures were more sensitive than perce...

Szczegółowa specyfikacja

Opis bibliograficzny
Główni autorzy: Bipasha Kashyap, Pubudu N. Pathirana, Malcolm Horne, Laura Power, David J. Szmulewicz
Format: Artykuł
Język:English
Wydane: IEEE 2021-01-01
Seria:IEEE Access
Hasła przedmiotowe:
Cerebellar ataxia
cerebellar dysarthria
clustering
mixed-effect modeling
mixture analysis
progression analysis
Dostęp online:https://ieeexplore.ieee.org/document/9541400/

Internet

https://ieeexplore.ieee.org/document/9541400/

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