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svm classification model  (Cognivue Inc)

 
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    Cognivue Inc svm classification model
    Svm Classification Model, supplied by Cognivue 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/product/svm+classification+model/svm+classification+model/pmc12089551-133-17-30
    Average 90 stars, based on 1 article reviews
    svm classification model - by Bioz Stars, 2026-10
    90/100 stars

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    Related Articles

    Derivative Assay:

    Article Title: The Cognivue Amyloid Risk Measure (CARM): A Novel Method to Predict the Presence of Amyloid with Cognivue Clarity
    Article Snippet: .. Combining methods from both classification and regression, the hyperplane separation strategy utilized coefficients derived from a trained SVM classification model [ ] to apply weights to each of the identified Cognivue measures. ..

    Article Title: The Cognivue Amyloid Risk Measure (CARM): A Novel Method to Predict the Presence of Amyloid with Cognivue Clarity.
    Article Snippet: .. Combining methods from both classification and regression, the hyperplane separation strategy utilized coefficients derived from a trained SVM classification model [28] to apply weights to each of the identified Cognivue measures. ..



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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