Predicting language treatment response in bilingual aphasia using neural network-based patient models
Abstract Predicting language therapy outcomes in bilinguals with aphasia (BWA) remains challenging due to the multiple pre- and poststroke factors that determine the deficits and recovery of their two languages. Computational models that simulate language impairment and treatment outcomes in BWA can...
Enregistré dans:
Auteurs principaux: | Uli Grasemann, Claudia Peñaloza, Maria Dekhtyar, Risto Miikkulainen, Swathi Kiran |
---|---|
Format: | article |
Langue: | EN |
Publié: |
Nature Portfolio
2021
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/7d581e2a474345e08945d1f3d7e77c5e |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Treatment for Anomia in Bilingual Speakers with Progressive Aphasia
par: Stephanie M. Grasso, et autres
Publié: (2021) -
Predicting language recovery in post-stroke aphasia using behavior and functional MRI
par: Michael Iorga, et autres
Publié: (2021) -
The Russian Aphasia Test: The first comprehensive, quantitative, standardized, and computerized aphasia language battery in Russian.
par: Maria V Ivanova, et autres
Publié: (2021) -
The Russian Aphasia Test: The first comprehensive, quantitative, standardized, and computerized aphasia language battery in Russian
par: Maria V. Ivanova, et autres
Publié: (2021) -
MOTHER LANGUAGE, SECONT LANGUAGE, BILINGUALISM, FOREIGN LANGUAGE
par: Şerif ORUÇ
Publié: (2019)