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Gi-Hun Park

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Strengthening Deep-Learning Models for Intracranial Hemorrhage Detection: Strongly Annotated Computed Tomography Images and Model Ensembles

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By Dong-Wan Kang, Wi-Sun Ryu, Dawid Schellingerhout, Gi-Hun Park
| Texas Medical Center
BACKGROUND AND PURPOSE: Multiple attempts at intracranial hemorrhage (ICH) detection using deep-learning techniques have been plagued by clinical failures. We aimed to compare the performance of a deep-learning algorithm for ICH detection trained on strongly and weakly annotated datasets, and to assess whether a weighted ensemble model that integrates separate models trained using datasets with different ICH improves performance.
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