The Postoperative Hyperopic Shift Risk Prediction Model for Primary Angle Closure Glaucoma Patients Based on Machine Learning
This study successfully developed a risk prediction model for HS after PE+IOL surgery in PACG patients based on various clinical features. The SVM and LR models show promising clinical application in predicting HS risk and can provide personalized postoperative management strategies for glaucoma surgery patients.
Authors
- Kuanrong Dang
- Jiantao Wang (ORCID: https://orcid.org/0000-0002-1929-3339)
- Di Gong (ORCID: https://orcid.org/0000-0002-7743-8460)
- Xiaoli Shen (ORCID: https://orcid.org/0000-0001-9541-3462)
- Junhong Guo (ORCID: https://orcid.org/0000-0003-2756-1855)
- Yijia Huang (ORCID: https://orcid.org/0000-0002-9657-7212)
- Simin Deng
- Yong Liu (ORCID: https://orcid.org/0000-0002-6173-8186)
Institutions
- Jinan University (CN)
- Southern Medical University Shenzhen Hospital (CN)
- First Affiliated Hospital of Jinan University (CN)
Publication Details
- Journal
- Journal of Glaucoma
- Published
- 2025-09-30
- DOI
- https://doi.org/10.1097/ijg.0000000000002648
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00