BloodNet improves ICH classification by modeling dependency between segmentation and classification tasks, reporting AUCs of 0.9493 and 0.9566 on held-out sets of over 1400 studies from more than 10 hospitals.
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Improved ICH classification using task-dependent learning
BloodNet improves ICH classification by modeling dependency between segmentation and classification tasks, reporting AUCs of 0.9493 and 0.9566 on held-out sets of over 1400 studies from more than 10 hospitals.