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svm model for classification  (Hamad Medical Corporation)

 
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    Hamad Medical Corporation svm model for classification
    Summary of the performance of AI models for assessment of stroke via retinal imaging.
    Svm Model For Classification, supplied by Hamad Medical Corporation, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/svm+model+for+classification/pmc11872910-15-8-15?v=Hamad+Medical+Corporation
    Average 90 stars, based on 1 article reviews
    svm model for classification - by Bioz Stars, 2026-07
    90/100 stars

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    1) Product Images from "Artificial intelligence in stroke risk assessment and management via retinal imaging"

    Article Title: Artificial intelligence in stroke risk assessment and management via retinal imaging

    Journal: Frontiers in Computational Neuroscience

    doi: 10.3389/fncom.2025.1490603

    Summary of the performance of AI models for assessment of stroke via retinal imaging.
    Figure Legend Snippet: Summary of the performance of AI models for assessment of stroke via retinal imaging.

    Techniques Used: Imaging, Extraction, Biomarker Discovery, Isolation



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    Image Search Results


    Summary of the performance of AI models for assessment of stroke via retinal imaging.

    Journal: Frontiers in Computational Neuroscience

    Article Title: Artificial intelligence in stroke risk assessment and management via retinal imaging

    doi: 10.3389/fncom.2025.1490603

    Figure Lengend Snippet: Summary of the performance of AI models for assessment of stroke via retinal imaging.

    Article Snippet: , 2022 , 56 (21/35/0) , OCT , SVM (Classification of pial collateral status) , Hamad General Hospital , 1. Retinal Vessel Multifractal Dimensions: Significantly higher in patients with poor pial collaterals compared to good pial collaterals. 2. SVM Model for classification: Accuracy = 0.743 Sensitivity = 0.743 Specificity = 0.707.

    Techniques: Imaging, Extraction, Biomarker Discovery, Isolation