Prediction Model for in-Stent Restenosis Post-PCI Based on Boruta Algorithm and Deep Learning: The Role of Blood Cholesterol and Lymphocyte Ratio
The CLR, as a biomarker that integrates lipid metabolism and inflammation, shows significant potential in predicting coronary ISR. The MLP model, based on deep learning, demonstrated robust predictive capabilities, offering new insights and strategies for clinical decision-making.
Authors
- Ling Hou (ORCID: https://orcid.org/0000-0001-6748-6314)
- Ke Su (ORCID: https://orcid.org/0000-0001-9503-7137)
- Yuanhong Li (ORCID: https://orcid.org/0000-0002-2215-3636)
- Jinbo Zhao (ORCID: https://orcid.org/0000-0002-7806-6072)
- Ting He (ORCID: https://orcid.org/0000-0001-6681-5083)
Institutions
- Hubei University of Medicine (CN)
- The Central Hospital of Enshi Tujia and Miao Autonomous Prefecture (CN)
Publication Details
- Journal
- Journal of Multidisciplinary Healthcare
- Published
- 2024-10-01
- DOI
- https://doi.org/10.2147/jmdh.s487511
- Citations
- 4
- Primary Topic
- Coronary Interventions and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 2.29