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...

Ausführliche Beschreibung

Bibliographische Detailangaben
Hauptverfasser: Bipasha Kashyap, Pubudu N. Pathirana, Malcolm Horne, Laura Power, David J. Szmulewicz
Format: Artikel
Sprache:English
Veröffentlicht: IEEE 2021-01-01
Schriftenreihe:IEEE Access
Schlagworte:
Cerebellar ataxia
cerebellar dysarthria
clustering
mixed-effect modeling
mixture analysis
progression analysis
Online Zugang:https://ieeexplore.ieee.org/document/9541400/

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