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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