CT-based deep learning model for predicting hospital discharge outcome in spontaneous intracerebral hemorrhage.
Xianjing ZhaoBijing ZhouYong LuoLei ChenLequn ZhuShixin ChangXiangming FangZhen-Wei YaoPublished in: European radiology (2023)
• Integrating clinical presentations, CT images, and radiological features to establish deep learning model for functional outcome prediction of patients with intracerebral hemorrhage. • Deep learning applied to CT images provides great help in prognosing functional outcome of intracerebral hemorrhage patients. • The developed deep learning model performs better than clinical prognostic scores in predicting functional outcome of patients with intracerebral hemorrhage.
Keyphrases
- deep learning
- convolutional neural network
- brain injury
- artificial intelligence
- image quality
- computed tomography
- dual energy
- machine learning
- contrast enhanced
- end stage renal disease
- newly diagnosed
- positron emission tomography
- chronic kidney disease
- magnetic resonance imaging
- magnetic resonance
- peritoneal dialysis