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Prediction of Adverse Events in Stable Non-Variceal Gastrointestinal Bleeding Using Machine Learning
Clinical risk-scoring systems are important for identifying patients with upper gastrointestinal bleeding (UGIB) who are at a high risk of hemodynamic instability. We developed an algorithm that predicts adverse events in patients with initially stable non-variceal UGIB using machine learning (ML)....
| Autores principales: | , , , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7464777/ https://www.ncbi.nlm.nih.gov/pubmed/32796647 http://dx.doi.org/10.3390/jcm9082603 |