ReviewTherapeutic advances in neurological disorders2020
Using artificial intelligence for improving stroke diagnosis in emergency departments: a practical framework.
Review in Therapeutic advances in neurological disorders, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 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
27 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The performance of machine learning for predicting the recurrent stroke: a systematic review and meta-analysis on 24,350 patients.Acta neurologica Belgica · 2025Pooled it
- Education Research: Validation of an AI-Powered Educational Platform for Neuroanatomical Localization and Stroke Syndrome Recognition: A Multicenter Study.Neurology. Education · 2026Article
- Review
- Advancing Spine Fracture Detection: The Role of Artificial Intelligence in Clinical Practice.Korean journal of neurotrauma · 2025Review
- The 100 highest-cited original articles in large vessel occlusions: A bibliometric analysis.The neuroradiology journal · 2025Review
- Artificial Intelligence and Neuroscience: Transformative Synergies in Brain Research and Clinical Applications.Journal of clinical medicine · 2025Review
- Early stroke detection through machine learning in the prehospital setting.Frontiers in cardiovascular medicine · 2025Article
- Review
- Clinician voices on ethics of LLM integration in healthcare: a thematic analysis of ethical concerns and implications.BMC medical informatics and decision making · 2024Article
- The Role of Artificial Intelligence-Powered Imaging in Cerebrovascular Accident Detection.Cureus · 2024Review
- Advancing Personalized Medicine by Analytical Means: Selection of Three Metabolites That Allows Discrimination between Glaucoma, Diabetes, and Controls.Metabolites · 2024Article
- Machine Learning-Based Prediction of Stroke in Emergency Departments.Therapeutic advances in neurological disorders · 2024Article
- Development and Validation of a Prediction Model on Adult Emergency Department Patients for Early Identification of Fulminant Myocarditis.Current medical science · 2023Article
- (VISIION-S): Viz.ai Implementation of Stroke augmented Intelligence and communications platform to improve Indicators and Outcomes for a comprehensive stroke center and Network - Sustainability.Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association · 2023Article
- Applications of Natural Language Processing for the Management of Stroke Disorders: Scoping Review.JMIR medical informatics · 2023Article
- Thoughts and Considerations of Studies on Smart Devices for Cerebrovascular Disease Detection and Progression Monitoring.Mayo Clinic proceedings. Digital health · 2023Article
- A Machine Learning Approach to Support Urgent Stroke Triage Using Administrative Data and Social Determinants of Health at Hospital Presentation: Retrospective Study.Journal of medical Internet research · 2023Article
- RETRACTED ARTICLE: Artificial intelligence in disease diagnosis: a systematic literature review, synthesizing framework and future research agenda.Journal of ambient intelligence and humanized computing · 2023Article
- A machine learning model for visualization and dynamic clinical prediction of stroke recurrence in acute ischemic stroke patients: A real-world retrospective study.Frontiers in neuroscience · 2023Article
- Evaluation of artificial intelligence techniques in disease diagnosis and prediction.Discover artificial intelligence · 2023Review
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
Abstract
Stroke is the fifth leading cause of death in the United States and a major cause of severe disability worldwide. Yet, recognizing the signs of stroke in an acute setting is still challenging and leads to loss of opportunity to intervene, given the narrow therapeutic window. A decision support system using artificial intelligence (AI) and clinical data from electronic health records combined with patients' presenting symptoms can be designed to support emergency department providers in stroke diagnosis and subsequently reduce the treatment delay. In this article, we present a practical framework to develop a decision support system using AI by reflecting on the various stages, which could eventually improve patient care and outcome. We also discuss the technical, operational, and ethical challenges of the process.
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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.