Fluid volume status detection model for patients with heart failure based on machine learning methods
Machine learning methods are effective in detecting fluid volume status in heart failure patients and can assist physicians with assisted diagnosis, thus helping clinicians to tailor precise management.
Authors
- Chao Feng (ORCID: https://orcid.org/0000-0003-4494-6845)
- Haozhe Huang (ORCID: https://orcid.org/0000-0003-1675-2170)
- Lu Chen (ORCID: https://orcid.org/0000-0002-5775-6947)
- Jing Guan (ORCID: https://orcid.org/0000-0003-2047-1937)
- Jinping Feng
- Ying Ao (ORCID: https://orcid.org/0000-0003-0644-9581)
Institutions
- Tianjin University (CN)
- Tianjin Chest Hospital (CN)
- Tianjin Medical University (CN)
Publication Details
- Journal
- Heliyon
- Published
- 2024-12-11
- DOI
- https://doi.org/10.1016/j.heliyon.2024.e41127
- Primary Topic
- Hemodynamic Monitoring and Therapy
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Tianjin University