ReviewBrain : a journal of neurology2022
Precision medicine in stroke: towards personalized outcome predictions using artificial intelligence.
Review in Brain : a journal of neurology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 106 papers, 8 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
106 citing papers in PubMed, 8 syntheses or guidelines pooled it, 173 citations in OpenAlex.
- Predictive Value of Machine Learning for Poststroke Mortality Risk: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- Ischemic stroke-specific cognitive dysfunction: a bibliometric analysis of research evolution.Frontiers in neurology · 2026Pooled it
- Accuracy of Machine Learning in Predicting Post-Stroke Depression: A Systematic Review and Meta-Analysis.Brain and behavior · 2025Pooled it
- Exploring the potential of machine learning and magnetic resonance imaging in early stroke diagnosis: a bibliometric analysis (2004-2023).Frontiers in neurology · 2025Pooled it
- Optimal training strategy for body weight support treadmill training to enhance lower limb motor function and activity of daily living in persons with stroke: a systematic review and meta-analysis of randomized controlled trials.Frontiers in neurology · 2025Pooled it
- Houston, We Have AI Problem! Quality Issues with Neuroimaging-Based Artificial Intelligence in Parkinson's Disease: A Systematic Review.Movement disorders : official journal of the Movement Disorder Society · 2024Pooled it
- Genomic insights and advanced machine learning: characterizing autism spectrum disorder biomarkers and genetic interactions.Metabolic brain disease · 2024Pooled it
- Machine learning in predicting outcomes for stroke patients following rehabilitation treatment: A systematic review.PloS one · 2023Pooled it
- EEG-fMRI neurofeedback versus motor imagery after stroke, a randomized controlled trial.Journal of neuroengineering and rehabilitation · 2025Trial
- Observational
- A Phenotype-Based Score to Prioritize RNF213 p.R4810K Genotyping in Isolated Intracranial Steno-Occlusive Disease.Translational stroke research · 2026Article
- Review and Meta-Analyses of the Effects of MLC601/MLC901 (NeuroAiD) on Post-Stroke Functional and Motor Recovery.Neurology international · 2026Review
- Multi-Omics Integration in Stroke: Neuroinflammatory Endotypes, Immune Cell Crosstalk, and Precision Biomarker Discovery.International journal of molecular sciences · 2026Review
- Artificial Intelligence That Changes Clinical Neurology Practice: Translating Algorithms Into Actionable Care.Journal of clinical neurology (Seoul, Korea) · 2026Review
- Artificial Intelligence and Emerging Digital Technologies Across the Stroke Continuum: From Risk Prediction to Real-Time Monitoring and Rapid Response.Medicina (Kaunas, Lithuania) · 2026Review
- Research Progress of Blood-Based Biomarkers for the Diagnosis and Prognostic Evaluation of Acute Ischemic Stroke.Biomolecules · 2026Review
- Estimating white matter hyperintensities volume in individuals with stroke using T1-weighted images.Neuroimage. Reports · 2026Article
- A clinical neuroimaging platform for rapid, automated lesion detection and personalized post-stroke outcome prediction.NPJ digital medicine · 2026Article
- Interpretable Machine Learning for Stroke Recovery: Predicting Discharge and 3-Month Functional Outcomes.NeuroRehabilitation · 2026Article
- Predicting post-stroke functional outcome using explainable machine learning and integrated data.Scientific reports · 2026Article
46 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Stroke ranks among the leading causes for morbidity and mortality worldwide. New and continuously improving treatment options such as thrombolysis and thrombectomy have revolutionized acute stroke treatment in recent years. Following modern rhythms, the next revolution might well be the strategic use of the steadily increasing amounts of patient-related data for generating models enabling individualized outcome predictions. Milestones have already been achieved in several health care domains, as big data and artificial intelligence have entered everyday life. The aim of this review is to synoptically illustrate and discuss how artificial intelligence approaches may help to compute single-patient predictions in stroke outcome research in the acute, subacute and chronic stage. We will present approaches considering demographic, clinical and electrophysiological data, as well as data originating from various imaging modalities and combinations thereof. We will outline their advantages, disadvantages, their potential pitfalls and the promises they hold with a special focus on a clinical audience. Throughout the review we will highlight methodological aspects of novel machine-learning approaches as they are particularly crucial to realize precision medicine. We will finally provide an outlook on how artificial intelligence approaches might contribute to enhancing favourable outcomes after stroke.
Indexed as
Identifiers
What OpenQuestion holds
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.