ReviewFrontiers in radiology2025
Use of artificial intelligence in the management of stroke: scoping review.
Review in Frontiers in radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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
5 citing papers in PubMed.
- Automated Multi-Modal MRI Segmentation of Stroke Lesions and Corticospinal Tract Integrity for Functional Outcome Prediction.Tomography (Ann Arbor, Mich.) · 2026Article
- Current State of the Clinical Applications of Artificial Intelligence in Stroke: A Literature Review.Brain sciences · 2026Review
- The Role of Artificial Intelligence in Stroke Imaging in Emergency Settings: A Systematic Review.Cureus · 2025Review
- Artificial Intelligence in Clinical Medicine: Challenges Across Diagnostic Imaging, Clinical Decision Support, Surgery, Pathology, and Drug Discovery.Clinics and practice · 2025Review
- An intervention study on the secondary prevention medication adherence of ischemic stroke patients based on the protection motivation theory combined with medication literacy education in the AI-HEALS: a randomized controlled trial protocol.Frontiers in public health · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Stroke is a condition that is more predominant in developed countries. However, it continues to be considered a high-cost health pathology worldwide, both in the medium and long term. Therefore, diagnosis, treatment, and rehabilitation are vital. Additionally, the assistance of artificial intelligence in these three principles has been increasing, given its effectiveness and efficiency in performance. Objective: This study analyzes the available evidence regarding the use of artificial intelligence in primary care for stroke patients. Methods: A scoping review was conducted on three indexed databases, Science Direct, Web of Science, and PubMed, resulting in the identification of 1,382 articles. Initially, these terms were filtered on the basis of the year of publication and language. A second distinction was subsequently made through the title and abstract of each publication. Results: A total of 33 articles summarizing 5 categories were selected: healthcare from a general point of view; stroke prediction; the diagnosis and treatment of both stroke and its sequelae; the risk of death in the poststroke period; and the assistance of AI in some specialties related to the disease. Conclusion: Artificial intelligence has the potential to improve stroke care, but more research is still needed to evaluate its performance in clinical practice. Introducción: El accidente cerebrovascular es una condición predominante en los países desarrollados. A pesar de esto, es una patología de salud de alto costo en todo el mundo, tanto a mediano como a largo plazo. Por lo tanto, el diagnóstico, el tratamiento y la rehabilitación son de vital importancia. Por lo anterior, la asistencia de la inteligencia artificial en estos tres principios ha ido en aumento, dada su eficacia y eficiencia en el desempeño. Objetivo: Este estudio analiza la evidencia disponible sobre el uso de la Inteligencia Artificial en la atención primaria para el accidente cerebrovascular. Métodos: Se realizó una revisión tipo Scoping Review en tres bases de datos indexadas: Science Direct, Web of Science y PubMed, lo que resultó en la identificación de 1,382 artículos. Inicialmente, estos se filtraron en función del año de publicación y el idioma. Posteriormente, se realizó una segunda distinción a través del título y el resumen de cada publicación. Resultados: Se seleccionaron un total de 33 artículos, que se seleccionaron en 5 categorías: atención médica desde un punto de vista general; predicción de accidente cerebrovascular; diagnóstico y tratamiento tanto del accidente cerebrovascular como de sus secuelas; riesgo de muerte en el período posterior al accidente cerebrovascular; y finalmente, la asistencia de la Inteligencia Artificial en algunas especialidades relacionadas con la enfermedad. Conclusión: La Inteligencia Artificial tiene el potencial de mejorar la atención del accidente cerebrovascular, pero aún se necesitan más investigaciones para evaluar su desempeño en la práctica clínica.
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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.