Image 1_Random forest-driven mortality prediction in critical IBD care: a dual-database model integrating comorbidity patterns and real-time physiometrics.jpeg

Image 1_Random forest-driven mortality prediction in critical IBD care: a dual-database model integrating comorbidity patterns and real-time physiometrics.jpeg

Background<p>Inflammatory bowel disease (IBD) poses significant mortality risks for critically ill patients requiring intensive care unit (ICU) admission, driven by complications such as malnutrition, thromboembolism, and multi-organ dysfunction. Current prognostic tools for mortality predicti...

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Bibliographic Details
Main Author: Zhenze Zhang (22011422) (author)
Other Authors: Caiqing Zhao (22011425) (author), Yijun Zhou (168788) (author), Ling Yao (16961) (author), Peng Liu (120506) (author), Ziling Fang (3690325) (author), Nian Fang (12959831) (author)
Published: 2025
Subjects:
Foetal Development and Medicine
machine learning
mortality prediction
critical care
nomogram
inflammatory bowel disease
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