Assessment of atherosclerosis risk in an insufficient sample size based on K-Means BS and TW-gcForest
Our approach can effectively improve accuracy, precision, recall, F1 score, and AUC compared with traditional algorithms.
Authors
- Hui Huang (ORCID: https://orcid.org/0000-0002-3130-3456)
- Lidan He (ORCID: https://orcid.org/0000-0002-7418-6886)
- Wenjun Liu (ORCID: https://orcid.org/0000-0002-4500-6559)
- Yudong Zhang (ORCID: https://orcid.org/0000-0002-4870-1493)
- Mengdie Yang
Institutions
- Nanjing University of Chinese Medicine (CN)
- Nanjing University of Information Science and Technology (CN)
Publication Details
- Journal
- Computer Methods in Biomechanics & Biomedical Engineering
- Published
- 2025-03-20
- DOI
- https://doi.org/10.1080/10255842.2025.2475478
- Citations
- 1
- Primary Topic
- Imbalanced Data Classification Techniques
- Type
- article
- Field-Weighted Citation Impact
- 2.48
Funders
- National Natural Science Foundation of China