ArticleFrontiers in neurology2020
Predicting 6-Month Unfavorable Outcome of Acute Ischemic Stroke Using Machine Learning.
Article in Frontiers in neurology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis 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
15 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine learning prediction of motor function in chronic stroke patients: a systematic review and meta-analysis.Frontiers in neurology · 2023Pooled it
- Predicting post-stroke functional outcome using explainable machine learning and integrated data.Scientific reports · 2026Article
- Machine learning-based prediction of activities of daily living in patients with stroke and other acquired brain injuries.Medicine · 2026Article
- Construction and Validation of a Risk Prediction Model Incorporating Temporal Muscle Thickness for Adverse Outcome in Acute Ischemic Stroke Patients.Journal of central nervous system disease · 2026Article
- Claims-Based Machine Learning Classifier of Modified Rankin Scale in Acute Ischemic Stroke.Journal of the American Heart Association · 2025Article
- Prediction of the short-term prognosis of acute ischaemic stroke in patients with high treatment platelet reactivity using explainable machine learning.Scientific reports · 2025Article
- AI post-intervention operational and functional outcomes prediction in ischemic stroke patients using MRIs.BMC medical imaging · 2025Article
- Predicting 3-month poor functional outcomes of acute ischemic stroke in young patients using machine learning.European journal of medical research · 2024Article
- Accurately predicting the risk of unfavorable outcomes after endovascular coil therapy in patients with aneurysmal subarachnoid hemorrhage: an interpretable machine learning model.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2024Article
- Improvement of predictive accuracies of functional outcomes after subacute stroke inpatient rehabilitation by machine learning models.PloS one · 2023Article
- Machine learning-based prediction of clinical outcomes after first-ever ischemic stroke.Frontiers in neurology · 2023Article
- Association of cognitive reserve with stroke outcome: a protocol for a systematic review.BMJ open · 2022Article
- Precision medicine in stroke: towards personalized outcome predictions using artificial intelligence.Brain : a journal of neurology · 2022Review
- Early Prediction of Functional Outcomes After Acute Ischemic Stroke Using Unstructured Clinical Text: Retrospective Cohort Study.JMIR medical informatics · 2022Article
- Natural Language Processing Enhances Prediction of Functional Outcome After Acute Ischemic Stroke.Journal of the American Heart Association · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
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.