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Peptic Ulcer Hemorrhage

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A Hybrid Residual Network and Long Short-Term Memory Method for Peptic Ulcer Bleeding Mortality Prediction.

AMIA ... Annual Symposium proceedings. AMIA Symposium 30815143
The prediction of patient mortality, which can detect high-risk patients, is a significant yet challenging problem in medical informatics. Thanks to the wide adoption of electronic health records (EHRs), many data-driven methods have been proposed to...
Algorithms Area Under Curve Electronic Health Records Humans Neural Networks, Computer Peptic Ulcer Hemorrhage Risk Assessment ROC Curve
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Importance-aware personalized learning for early risk prediction using static and dynamic health data.

Journal of the American Medical Informatics Association : JAMIA 33496786
OBJECTIVE: Accurate risk prediction is important for evaluating early medical treatment effects and improving health care quality. Existing methods are usually designed for dynamic medical data, which require long-term observations. Meanwhile, import...
Data Mining Datasets as Topic Deep Learning Humans Models, Theoretical Neural Networks, Computer Peptic Ulcer Hemorrhage Precision Medicine Prognosis Risk Assessment
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Artificial intelligence-assisted assessment for Forrest classification of peptic ulcer bleeding: hype or reality?

Endoscopy 38479415
Artificial Intelligence Humans Peptic Ulcer Hemorrhage
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A fusion model of manually extracted visual features and deep learning features for rebleeding risk stratification in peptic ulcers.

Nan fang yi ke da xue xue bao = Journal of Southern Medical University 39819728
OBJECTIVES: We propose a multi-feature fusion model based on manually extracted features and deep learning features from endoscopic images for grading rebleeding risk of peptic ulcers.
Deep Learning Humans Peptic Ulcer Peptic Ulcer Hemorrhage Recurrence Risk Assessment
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