Predicting Cycloplegic Spherical Equivalent Refraction Among Children and Adolescents Using Non-cycloplegic Data and Machine Learning — China, 2020–2024
Machine learning models incorporating noncycloplegic SE and ocular biometrics accurately estimate cycloplegic SE in children and adolescents, providing a practical alternative for large-scale refractive-error surveillance when cycloplegia is impractical.
Authors
- Ran Qin
- Bingjie Sun (ORCID: https://orcid.org/0000-0003-3536-0041)
- Xin Guo (ORCID: https://orcid.org/0000-0002-2700-2167)
- Chengyu Zhang (ORCID: https://orcid.org/0000-0001-7257-9689)
- Keke Liu (ORCID: https://orcid.org/0000-0003-2222-5940)
- Luo Huijuan
- Kuang Huining
- E Ranbo
Institutions
- Capital Medical University (CN)
- Chinese Center For Disease Control and Prevention (CN)
- Beijing Center for Disease Prevention and Control (CN)
Publication Details
- Journal
- China CDC Weekly
- Published
- 2025-01-01
- DOI
- https://doi.org/10.46234/ccdcw2025.217
- Primary Topic
- Traditional Chinese Medicine Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00