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svm classification model based on features of total head and body movement and general facial expressiveness  (Movex Inc)

 
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    Movex Inc svm classification model based on features of total head and body movement and general facial expressiveness
    Svm Classification Model Based On Features Of Total Head And Body Movement And General Facial Expressiveness, supplied by Movex Inc, 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/result/svm classification model based on features of total head and body movement and general facial expressiveness/product/Movex Inc
    Average 90 stars, based on 1 article reviews
    svm classification model based on features of total head and body movement and general facial expressiveness - by Bioz Stars, 2026-04
    90/100 stars

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    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