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Deep learning for collateral evaluation in ischemic stroke with imbalanced data

Author(s): Aktar M; Reyes J; Tampieri D; Rivaz H; Xiao Y; Kersten-Oertel M;

Purpose: Collateral evaluation is typically done using visual inspection of cerebral images and thus suffers from intra- and inter-rater variability. Large open databases of ischemic stroke patients are rare, limiting the use of deep learning methods in treatment decision-making.
Methods: We adapted a pre-trained Eff ...

Article GUID: 36635594


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