Prediction of Adverse Events in Stable Non-Variceal Gastrointestinal Bleeding Using Machine Learning

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)....

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Bibliographic Details
Main Authors: Dong-Woo Seo, Hahn Yi, Beomhee Park, Youn-Jung Kim, Dae Ho Jung, Ilsang Woo, Chang Hwan Sohn, Byuk Sung Ko, Namkug Kim, Won Young Kim
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:Journal of Clinical Medicine
Subjects:
emergency departments
machine learning
upper gastrointestinal bleeding
mortality
hypotension
endoscopy
Online Access:https://www.mdpi.com/2077-0383/9/8/2603

Internet

https://www.mdpi.com/2077-0383/9/8/2603

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