Development and validation of machine learning for pathological changes in high myopia patients with tessellated fundus: a cross-sectional study
Machine learning models using lifestyle and clinical parameters can effectively screen for early pathological changes in high myopia with tessellated fundus, offering an auxiliary tool for clinicians.
Authors
- Feng Bi (ORCID: https://orcid.org/0000-0002-1604-7108)
- Huiyi Zuo (ORCID: https://orcid.org/0000-0002-0447-2879)
- Xin Liu (ORCID: https://orcid.org/0000-0001-8323-7289)
- Jian He
- Lijia Huang (ORCID: https://orcid.org/0000-0003-2818-940X)
- Baoyu Huang (ORCID: https://orcid.org/0000-0003-3225-0138)
- Mei‐Hua Huang (ORCID: https://orcid.org/0009-0003-9028-6857)
- Hai Huang
Institutions
- The People's Hospital of Guangxi Zhuang Autonomous Region (CN)
- First Affiliated Hospital of GuangXi Medical University (CN)
Publication Details
- Journal
- Graefe s Archive for Clinical and Experimental Ophthalmology
- Published
- 2025-10-03
- DOI
- https://doi.org/10.1007/s00417-025-06988-2
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Natural Science Foundation of Guangxi Province