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Intra-Domain Task-Adaptive Transfer Learning to Determine Acute Ischemic Stroke Onset Time
We apply this approach to both 2D and 3D CNN architectures with our top model achieving an ROC-AUC value of 0. 74, with a sensitivity of 0. 70 and a specificity of 0. 81 for classifying TSS < 4. 5 hours.
Predicting Thrombectomy Recanalization from CT Imaging Using Deep Learning Models
This is a promising result that supports future applications of deep learning on CT and CTA for the identification of eligible AIS patients for MTB.
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