首页|期刊导航|World Journal of Emergency Medicine|Development and validation of an interpretable machine learning model to predict high-risk patients with acute small bowel obstruction

Development and validation of an interpretable machine learning model to predict high-risk patients with acute small bowel obstruction

Yingsong Zhao Hongda Wang Eryang Zhao Guangyu Zhao Junrong Zhang Sanyang Chen Yang Li Yong Zhao Wenfeng Zhuo Guozheng Lyu Ping Hu Gang Zhao

World Journal of Emergency Medicine2026，Vol.17Issue(4)：P.344-352,9.

World Journal of Emergency Medicine2026，Vol.17Issue(4)：P.344-352,9.DOI:10.5847/wjem.j.1920-8642.2026.063

Development and validation of an interpretable machine learning model to predict high-risk patients with acute small bowel obstruction

Yingsong Zhao ¹Hongda Wang ¹Eryang Zhao ¹Guangyu Zhao ¹Junrong Zhang ²Sanyang Chen ³Yang Li ¹Yong Zhao ¹Wenfeng Zhuo ¹Guozheng Lyu ¹Ping Hu ¹Gang Zhao¹

作者信息

1. Department of Emergency Surgery,Union Hospital,Tongji Medical College,Huazhong University of Science and Technology,Wuhan 430022,China
2. Department of Emergency Surgery,Fujian Medical University Union Hospital,Fuzhou 350001,China
3. Department of Emergency,the First Affiliated Hospital of Zhengzhou University,Zhengzhou 450052,China
折叠

摘要

关键词

Small bowel obstruction/Machine learning/Prediction model

分类

医药卫生

引用本文复制引用

Yingsong Zhao,Hongda Wang,Eryang Zhao,Guangyu Zhao,Junrong Zhang,Sanyang Chen,Yang Li,Yong Zhao,Wenfeng Zhuo,Guozheng Lyu,Ping Hu,Gang Zhao..Development and validation of an interpretable machine learning model to predict high-risk patients with acute small bowel obstruction[J].World Journal of Emergency Medicine,2026,17(4):P.344-352,9.

基金项目

supported by grants from the Clinical Research Physician Program of Tongji Medical College （）

Huazhong University of Science and Technology (to GZ)。（to GZ）

World Journal of Emergency Medicine

ISSN：1920-8642

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