ReviewFrontiers in neurology2024
Artificial intelligence in ischemic stroke images: current applications and future directions.
Review in Frontiers in neurology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Deep-learning-based non-contrast CT for detecting acute ischemic stroke: a systematic review and HSROC meta-analysis of patient-level diagnostic accuracy.BMC neurology · 2025Pooled it
- The Role of AI-Based Software BrainScan in the Interpretation of Non-Contrast Head CT in Acute Ischemic Stroke: An External Validation Study.Neurology international · 2026Article
- Comparing deep learning stroke segmentation in NCCT, CTA, and CTP: Accuracy, domain transfer, and temporal sampling effect.Medical physics · 2026Article
- Influence of deep learning image reconstruction and adaptive statistical iterative reconstruction-V on automated Alberta stroke program early CT score- evaluation.Neuroradiology · 2026Article
- Research Progress on Radiofrequency Treatment of Primary Trigeminal Neuralgia in the V2 Maxillary Nerve.Pain and therapy · 2026Review
- Current State of the Clinical Applications of Artificial Intelligence in Stroke: A Literature Review.Brain sciences · 2026Review
- Integration of imaging and clinical biomarkers for cerebral infarction diagnosis via NeuroFusionNet.Frontiers in neuroscience · 2026Article
- Lightweight deep learning framework for intracranial hemorrhage detection in brain CT scans.Frontiers in medicine · 2026Article
- Factors Influencing Stroke Severity Based on Collateral Circulation, Clinical Markers and Machine Learning.Diagnostics (Basel, Switzerland) · 2025Article
- Emergency radiology: roadmap for radiology departments.Japanese journal of radiology · 2025Review
- Review
- Artificial Intelligence in Vascular Neurology: Applications, Challenges, and a Review of AI Tools for Stroke Imaging, Clinical Decision Making, and Outcome Prediction Models.Current neurology and neuroscience reports · 2025Review
- Non-Contrast Computed Tomography-Based Triage and Notification for Large Vessel Occlusion Stroke: A Before and After Study Utilizing Artificial Intelligence on Treatment Times and Outcomes.Journal of clinical medicine · 2025Article
- Multi-Modality Fusion and Tumor Sub-Component Relationship Ensemble Network for Brain Tumor Segmentation.Bioengineering (Basel, Switzerland) · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This paper reviews the current research progress in the application of Artificial Intelligence (AI) based on ischemic stroke imaging, analyzes the main challenges, and explores future research directions. This study emphasizes the application of AI in areas such as automatic segmentation of infarct areas, detection of large vessel occlusion, prediction of stroke outcomes, assessment of hemorrhagic transformation risk, forecasting of recurrent ischemic stroke risk, and automatic grading of collateral circulation. The research indicates that Machine Learning (ML) and Deep Learning (DL) technologies have tremendous potential for improving diagnostic accuracy, accelerating disease identification, and predicting disease progression and treatment responses. However, the clinical application of these technologies still faces challenges such as limitations in data volume, model interpretability, and the need for real-time monitoring and updating. Additionally, this paper discusses the prospects of applying large language models, such as the transformer architecture, in ischemic stroke imaging analysis, emphasizing the importance of establishing large public databases and the need for future research to focus on the interpretability of algorithms and the comprehensiveness of clinical decision support. Overall, AI has significant application value in the management of ischemic stroke; however, existing technological and practical challenges must be overcome to achieve its widespread application in clinical practice.
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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.