Machine learning for predicting in-hospital mortality in elderly patients with heart failure combined with hypertension: a multicenter retrospective study
This study developed eight machine learning models to predict in-hospital mortality in elderly patients with hypertension as well as heart failure. Compared to other algorithms, the Random Forest model performed significantly better. Our study successfully predicted in-hospital mortality and identified the factors most associated with in-hospital mortality.
Authors
- Zulong Xie
- Jie Yu (ORCID: https://orcid.org/0000-0001-8100-8896)
- Xiaoqian Zhou
- Tianyu Xiang
- Jian Huang (ORCID: https://orcid.org/0000-0002-4300-7128)
- Yang Zhang (ORCID: https://orcid.org/0000-0002-1317-120X)
- Lirong Kuang
- Huan Li (ORCID: https://orcid.org/0009-0002-3838-0267)
- Xiaozhu Liu (ORCID: https://orcid.org/0000-0002-7800-3100)
- Niying Yin
- Yuxin Zou
- Xiujuan Li (ORCID: https://orcid.org/0000-0002-2689-1193)
Institutions
- Qingdao University (CN)
- Capital Medical University (CN)
- Dalian Medical University (CN)
- Wenzhou Medical University (CN)
- First Affiliated Hospital of Wenzhou Medical University (CN)
- Sir Run Run Shaw Hospital (CN)
- Second Affiliated Hospital of Chongqing Medical University (CN)
- Ruian People's Hospital (CN)
- National Blood Transfusion Service (NG)
- Wuchang University of Technology (CN)
- Taian City Central Hospital (CN)
- Beijing Shijitan Hospital (CN)
- Wuhan University of Science and Technology (CN)
- Zhejiang University (CN)
- Chongqing Medical University (CN)
Publication Details
- Journal
- Cardiovascular Diabetology
- Published
- 2024-11-15
- DOI
- https://doi.org/10.1186/s12933-024-02503-9
- Citations
- 24
- Primary Topic
- Blood Pressure and Hypertension Studies
- Type
- article
- Field-Weighted Citation Impact
- 9.65
Funders
- Chongqing Medical University