AIMC Topic: Language Therapy

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Machine Learning Predictions of Recovery in Bilingual Poststroke Aphasia: Aligning Insights With Clinical Evidence.

Stroke Jan 2, 2025
BACKGROUND: Predicting treated language improvement (TLI) and transfer to the untreated language (cross-language generalization, CLG) after speech-language therapy in bilingual individuals with poststroke aphasia is crucial for personalized treatment...
Humans Machine Learning Female Aged Adult Male Middle Aged Treatment Outcome Recovery of Function Stroke Multilingualism Stroke Rehabilitation Aphasia Language Therapy
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Identifiable Patterns of Trait, State, and Experience in Chronic Stroke Recovery.

Neurorehabilitation and neural repair Dec 22, 2020
BACKGROUND: Considerable evidence indicates that the functional connectome of the healthy human brain is highly stable, analogous to a fingerprint.
Humans Female Aged Adult Male Middle Aged Support Vector Machine Magnetic Resonance Imaging Chronic Disease Ischemic Stroke Outcome Assessment, Health Care Individuality Connectome Stroke Rehabilitation Aphasia Language Therapy
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Identifying Children With Clinical Language Disorder: An Application of Machine-Learning Classification.

Journal of learning disabilities May 7, 2019
In this study, we identified child- and family-level characteristics most strongly associated with clinical identification of language disorder for preschool-aged children. We used machine learning to identify variables that best classified children ...
Humans Machine Learning Female Male Child, Preschool Outcome Assessment, Health Care Early Diagnosis Early Medical Intervention Language Development Disorders Language Therapy
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