Improving cardiovascular risk prediction with machine learning: a focus on perivascular adipose tissue characteristics
The developed ensemble model effectively predicted MACE incidence based on clinical and imaging features, highlighting the potential of ML algorithms in cardiovascular risk prediction and personalized medicine. Early identification of high-risk patients may facilitate targeted preventive interventions and improve patient outcomes.
Authors
- Zefeng Lu (ORCID: https://orcid.org/0000-0002-3139-4546)
- Hongwei Xu (ORCID: https://orcid.org/0000-0002-1692-713X)
- Linfeng Fu
- Cong He (ORCID: https://orcid.org/0000-0003-1088-8915)
- Lingting Kong
- Fangye Wu
- Yingpeng Qi
Institutions
- Shaoxing Second Hospital (CN)
Publication Details
- Journal
- BioMedical Engineering OnLine
- Published
- 2024-08-05
- DOI
- https://doi.org/10.1186/s12938-024-01273-5
- Citations
- 4
- Primary Topic
- Cardiovascular Disease and Adiposity
- Type
- article
- Field-Weighted Citation Impact
- 1.61