Prognosis of major bleeding based on residual variables and machine learning for critical patients with upper gastrointestinal bleeding: A multicenter study
ML models using residuals improved the accuracy and interpretability in predicting major bleeding during ICU admission in patients with UGIB. These interpretable features may facilitate the early identification and management of high-risk patients, thereby improving hemodynamic stability and outcomes.
Authors
- Fuxing Deng (ORCID: https://orcid.org/0000-0002-5490-5695)
- Yaoyuan Cao (ORCID: https://orcid.org/0009-0003-4727-1991)
- Shuangping Zhao (ORCID: https://orcid.org/0000-0003-1258-8852)
- Hui Wang (ORCID: https://orcid.org/0009-0006-3512-9308)
Institutions
- Central South University (CN)
- Changsha Medical University (CN)
- Xiangya Hospital Central South University (CN)
Publication Details
- Journal
- Journal of Critical Care
- Published
- 2024-10-02
- DOI
- https://doi.org/10.1016/j.jcrc.2024.154923
- Citations
- 5
- Primary Topic
- Gastrointestinal Bleeding Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 2.32