Predicting lymphovascular space invasion in early-stage cervical squamous cell carcinoma using heart rate variability
The Logistic model constructed based on HRV features has a relatively good diagnostic performance in predicting the LVSI status of ECSCC, but further research is still needed through larger datasets, more features, and the combination of machine learning models.
Authors
- Yifang Zhang
- Zhijing Song
- Bo Shi (ORCID: https://orcid.org/0000-0002-0780-0372)
- Min Liu (ORCID: https://orcid.org/0000-0002-8077-0130)
- Sai Zhang (ORCID: https://orcid.org/0000-0002-8028-4183)
- Jian Liu (ORCID: https://orcid.org/0000-0002-8969-8446)
- Junlong Fang (ORCID: https://orcid.org/0009-0002-2627-4424)
Institutions
- Bengbu Medical College (CN)
- First Affiliated Hospital of Bengbu Medical College (CN)
Publication Details
- Journal
- Frontiers in Oncology
- Published
- 2025-07-21
- DOI
- https://doi.org/10.3389/fonc.2025.1562347
- Primary Topic
- Heart Rate Variability and Autonomic Control
- Type
- article
- Field-Weighted Citation Impact
- 0.00