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Neurologists-level interpretable CT-based deep neural network for prediction of hemorrhagic transformation after ischemic stroke
0
Zitationen
8
Autoren
2026
Jahr
Abstract
By combining plain CT scans with deep learning methodologies, we developed a clinically applicable model with demonstrable interpretability. Primarily designed to predict HT after acute ischemic stroke, this model demonstrated significant performance advantages in testing compared to both clinical physicians and similar existing models.
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Autoren
Institutionen
- Beijing Tian Tan Hospital(CN)
- National Clinical Research Center for Digestive Diseases(CN)
- Capital Medical University(CN)
- Shanghai Jiao Tong University(CN)
- The People's Hospital of Guangxi Zhuang Autonomous Region(CN)
- Shanghai University(CN)
- Academy of Medical Sciences(GB)
- Academia Sinica(TW)
- Chinese Academy of Medical Sciences & Peking Union Medical College(CN)