Prediction Models of Microinvasive Cervical Cancer in High-Grade Squamous Intraepithelial Lesion Treatment by Loop Electrosurgical Excision Procedure
The machine learning-based model can accurately assess the risk of MIC during the treatment of HSIL with LEEP, potentially aiding in the selection of appropriate treatment and surveillance strategies in clinical practice.
Authors
- Mingzhu Huang (ORCID: https://orcid.org/0000-0002-0437-5737)
- Xiaohong Chen (ORCID: https://orcid.org/0009-0004-6266-2031)
- Rong‐Long Wang (ORCID: https://orcid.org/0009-0004-6354-3632)
- Youzhong Zhang (ORCID: https://orcid.org/0000-0002-6132-141X)
- Wei Chen (ORCID: https://orcid.org/0000-0002-1281-3389)
- Yu‐Xiang Yang (ORCID: https://orcid.org/0009-0003-3614-2713)
- Xin Lin (ORCID: https://orcid.org/0000-0002-0594-6319)
- Lu Liu (ORCID: https://orcid.org/0009-0001-6127-3999)
Institutions
- Fujian Medical University (CN)
- Zhangzhou Municipal Hospital of Fujian Province (CN)
- Second Hospital of Shandong University (CN)
- Qilu Hospital of Shandong University (CN)
- Shandong First Medical University (CN)
Publication Details
- Journal
- Risk Management and Healthcare Policy
- Published
- 2025-09-01
- DOI
- https://doi.org/10.2147/rmhp.s536347
- Primary Topic
- Endometrial and Cervical Cancer Treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Shandong Province
- Fujian Medical University
- Science and Technology Development Plan of Shandong Province