ArticleNature human behaviour2020
Investigating the effect of changing parameters when building prediction models for post-stroke aphasia.
Article in Nature human behaviour, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
24 citing papers in PubMed, 47 citations in OpenAlex.
- Diagnosing and managing post-stroke aphasia.Expert review of neurotherapeutics · 2021Trial
- Applications of Artificial Intelligence in Neurological Voice Disorders.World journal of otorhinolaryngology - head and neck surgery · 2025Review
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- Article
- An Introduction to Machine Learning for Speech-Language Pathologists: Concepts, Terminology, and Emerging Applications.Perspectives of the ASHA special interest groups · 2025Article
- Predicting individual long-term prognosis of spatial neglect based on acute stroke patient data.Brain communications · 2025Article
- Benchmarking machine learning models in lesion-symptom mapping for predicting language outcomes in stroke survivors.Frontiers in neuroimaging · 2025Article
- Structural Disconnections Caused by White Matter Hyperintensities in Post-Stroke Spatial Neglect.Human brain mapping · 2024Article
- Establishing and evaluating the gradient of item naming difficulty in post-stroke aphasia and semantic dementia.Cortex; a journal devoted to the study of the nervous system and behavior · 2024Article
- Multivariate lesion symptom mapping for predicting trajectories of recovery from aphasia.Brain communications · 2024Article
- Using in vivo functional and structural connectivity to predict chronic stroke aphasia deficits.Brain : a journal of neurology · 2023Article
- Mapping lesion, structural disconnection, and functional disconnection to symptoms in semantic aphasia.Brain structure & function · 2022Article
- Efficient and effective assessment of deficits and their neural bases in stroke aphasia.Cortex; a journal devoted to the study of the nervous system and behavior · 2022Article
- The multidimensional nature of aphasia recovery post-stroke.Brain : a journal of neurology · 2022Article
- Multimodal Neural and Behavioral Data Predict Response to Rehabilitation in Chronic Poststroke Aphasia.Stroke · 2022Article
- Predictors of Therapy Response in Chronic Aphasia: Building a Foundation for Personalized Aphasia Therapy.Journal of stroke · 2022Review
- Characterising factors underlying praxis deficits in chronic left hemisphere stroke patients.Cortex; a journal devoted to the study of the nervous system and behavior · 2021Article
- A Bayesian optimization approach for rapidly mapping residual network function in stroke.Brain : a journal of neurology · 2021Article
- Temporal variability of regional intrinsic neural activity in drug-naïve patients with obsessive-compulsive disorder.Human brain mapping · 2021Article
- Machine learning-based multimodal prediction of language outcomes in chronic aphasia.Human brain mapping · 2021Article
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
Neuroimaging has radically improved our understanding of how speech and language abilities map to the brain in normal and impaired participants, including the diverse, graded variations observed in post-stroke aphasia. A handful of studies have begun to explore the reverse inference: creating brain-to-behaviour prediction models. In this study, we explored the effect of three critical parameters on model performance: (1) brain partitions as predictive features, (2) combination of multimodal neuroimaging and (3) type of machine learning algorithms. We explored the influence of these factors while predicting four principal dimensions of language and cognition variation in post-stroke aphasia. Across all four behavioural dimensions, we consistently found that prediction models derived from diffusion-weighted data did not improve performance over models using structural measures extracted from T1 scans. Our results provide a set of principles to guide future work aiming to predict outcomes in neurological patients from brain imaging data.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.