Development and validation of a machine learning model to predict hemostatic intervention in patients with acute upper gastrointestinal bleeding

Development and validation of a machine learning model to predict hemostatic intervention in patients with acute upper gastrointestinal bleeding

Abstract Background Acute upper gastrointestinal bleeding (UGIB) is common in clinical practice and has a wide range of severity. Along with medical therapy, endoscopic intervention is the mainstay treatment for hemostasis in high-risk rebleeding lesions. Predicting the need for endoscopic intervent...

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Bibliographic Details
Main Authors: Kajornvit Raghareutai, Watcharaporn Tanchotsrinon, Onuma Sattayalertyanyong, Uayporn Kaosombatwattana
Format: Article
Language:English
Published: BMC 2025-03-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Machine learning
Upper GI bleeding
UGIB
Endoscopic intervention
Prediction
Online Access:https://doi.org/10.1186/s12911-025-02969-x
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https://doi.org/10.1186/s12911-025-02969-x

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