ArticleFrontiers in neurology2024
Ischemic stroke outcome prediction with diversity features from whole brain tissue using deep learning network.
Article 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 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Radiomics and ischemic stroke research: bibliometric insights and visual trends (2004-2024).Frontiers in neurology · 2025Pooled it
- Multi-dimensional MRI representation and privileged learning approaches to functional outcome prediction for ischemic stroke patients.NPJ digital medicine · 2026Article
- Enhanced preoperative prediction for microvascular invasion in hepatocellular carcinoma through an optimized MR Radiomics combination strategy and machine learning predictor.Frontiers in medicine · 2026Article
- Dual-level weighted cross-entropy loss function and multi-object region segmentation network evaluation for dynamic knee joint X-ray radiography based on a novel scoring criterion.Frontiers in medicine · 2026Article
- Correlation between neuroimaging, neurological deficits, and neurotrophic proteins in predicting rehabilitation potential in ischemic stroke patients.Quantitative imaging in medicine and surgery · 2025Article
- AI post-intervention operational and functional outcomes prediction in ischemic stroke patients using MRIs.BMC medical imaging · 2025Article
- Machine learning-based prognostic prediction for acute ischemic stroke using whole-brain and infarct multi-PLD ASL radiomics.BMC medical imaging · 2025Article
- Automatic prediction of stroke treatment outcomes: latest advances and perspectives.Biomedical engineering letters · 2025Review
- Stroke-SCORE: Personalizing Acute Ischemic Stroke Treatment to Improve Patient Outcomes.Journal of personalized medicine · 2025Article
- Three-stage registration pipeline for dynamic lung field of chest X-ray images based on convolutional neural networks.Frontiers in artificial intelligence · 2025Article
- Blood-brain barrier breakdown in brain ischemia: Insights from MRI perfusion imaging.Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics · 2025Review
- The impracticality of radiomics research in acute ischemic stroke: from the perspective of primary healthcare institutions.Frontiers in neurology · 2025Review
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Authors and funding
2 authors.
Funding
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Abstract
Objectives: This study proposed an outcome prediction method to improve the accuracy and efficacy of ischemic stroke outcome prediction based on the diversity of whole brain features, without using basic information about patients and image features in lesions. Design: In this study, we directly extracted dynamic radiomics features (DRFs) from dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) and further extracted static radiomics features (SRFs) and static encoding features (SEFs) from the minimum intensity projection (MinIP) map, which was generated from the time dimension of DSC-PWI images. After selecting whole brain features F Results: The experimental results show that the feature F Conclusion: The method used in our study can achieve an accurate assessment of stroke outcomes without segmentation of ischemic lesions, which is of great significance for rapid, efficient, and accurate clinical stroke treatment.
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