AIMC Topic: Aphasia

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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...
Aged Adult Male Middle Aged Humans Machine Learning Female Multilingualism Stroke Rehabilitation Aphasia Language Therapy Treatment Outcome Recovery of Function Stroke
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AI-assisted assessment and treatment of aphasia: a review.

Frontiers in public health Aug 29, 2024
Aphasia is a language disorder caused by brain injury that often results in difficulties with speech production and comprehension, significantly impacting the affected individuals' lives. Recently, artificial intelligence (AI) has been advancing in m...
Humans Artificial Intelligence Machine Learning Natural Language Processing Aphasia
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Clinical efficacy of pre-trained large language models through the lens of aphasia.

Scientific reports Jul 6, 2024
The rapid development of large language models (LLMs) motivates us to explore how such state-of-the-art natural language processing systems can inform aphasia research. What kind of language indices can we derive from a pre-trained LLM? How do they d...
Humans Natural Language Processing Aphasia Language Models, Theoretical
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Discourse- and lesion-based aphasia quotient estimation using machine learning.

NeuroImage. Clinical Apr 6, 2024
Discourse is a fundamentally important aspect of communication, and discourse production provides a wealth of information about linguistic ability. Aphasia commonly affects, in multiple ways, the ability to produce discourse. Comprehensive aphasia as...
Adult Male Middle Aged Magnetic Resonance Imaging Brain Female Aged Neuropsychological Tests Language Tests Aphasia Humans Machine Learning
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Machine learning-based multimodal prediction of language outcomes in chronic aphasia.

Human brain mapping Dec 30, 2020
Recent studies have combined multiple neuroimaging modalities to gain further understanding of the neurobiological substrates of aphasia. Following this line of work, the current study uses machine learning approaches to predict aphasia severity and ...
Support Vector Machine Magnetic Resonance Imaging Multimodal Imaging Outcome Assessment, Health Care Neuroimaging Chronic Disease Humans Aphasia Stroke Female Cerebrovascular Circulation Aged Diffusion Tensor Imaging Severity of Illness Index Aged, 80 and over Language Tests Male Functional Neuroimaging Adult Middle Aged
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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.
Stroke Rehabilitation Aphasia Language Therapy Outcome Assessment, Health Care Individuality Connectome Humans Adult Chronic Disease Female Male Ischemic Stroke Aged Support Vector Machine Middle Aged Magnetic Resonance Imaging
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An Efficient Deep Learning Based Method for Speech Assessment of Mandarin-Speaking Aphasic Patients.

IEEE journal of biomedical and health informatics Nov 4, 2020
Speech assessment is an important part of the rehabilitation process for patients with aphasia (PWA). Mandarin speech lucidity features such as articulation, fluency, and tone influence the meaning of the spoken utterance and overall speech clarity. ...
Humans Speech Aphasia Neural Networks, Computer Language Deep Learning
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The neural and neurocomputational bases of recovery from post-stroke aphasia.

Nature reviews. Neurology Nov 26, 2019
Language impairment, or aphasia, is a disabling symptom that affects at least one third of individuals after stroke. Some affected individuals will spontaneously recover partial language function. However, despite a growing number of investigations, ...
Recovery of Function Stroke Aphasia Humans Neural Networks, Computer Brain
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Predicting the sources of impaired wh-question comprehension in non-fluent aphasia: A cross-linguistic machine learning study on Turkish and German.

Cognitive neuropsychology Nov 15, 2017
This study investigates the comprehension of wh-questions in individuals with aphasia (IWA) speaking Turkish, a non-wh-movement language, and German, a wh-movement language. We examined six German-speaking and 11 Turkish-speaking IWA using picture-po...
Middle Aged Aged Linguistics Comprehension Adult Humans Turkey Movement Aphasia Male Machine Learning Germany Female
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Detecting Post-Stroke Aphasia Via Brain Responses to Speech in a Deep Learning Framework.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Aphasia, a language disorder primarily caused by a stroke, is traditionally diagnosed using behavioral language tests. However, these tests are time-consuming, require manual interpretation by trained clinicians, suffer from low ecological validity, ...
Humans Brain Female Aged Stroke Aphasia Deep Learning Adult Speech Male Middle Aged Support Vector Machine Electroencephalography
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