Quantifying optimal inner limiting membrane peeling in macular hole surgery: a machine learning framework for predictive modeling and schematic visualization
The Ridge Regression model effectively predicts the optimal ILM peeling radius. The integration of schematic diagram generation enhances surgical planning and provides valuable educational resources, highlighting the potential of machine learning and visualization tools in improving MH surgery outcomes.
Authors
- Le-dong Zhao
- Hongjie Ma (ORCID: https://orcid.org/0000-0001-8507-3636)
- Zhaoxiong Wang (ORCID: https://orcid.org/0000-0001-6154-507X)
- Bojie Hu (ORCID: https://orcid.org/0000-0001-7840-8290)
- Zetong Nie
- Wenbo Li (ORCID: https://orcid.org/0009-0001-7945-4958)
- Lin Song (ORCID: https://orcid.org/0000-0003-4600-2813)
- Xiaorong Li (ORCID: https://orcid.org/0000-0003-0641-2797)
- Chen Lü (ORCID: https://orcid.org/0000-0003-1927-2391)
- Xiang Zhang (ORCID: https://orcid.org/0000-0003-4245-8936)
- Chang Liu (ORCID: https://orcid.org/0000-0003-0650-1773)
Institutions
- Tianjin Medical University Eye Hospital (CN)
- Tianjin Medical University (CN)
- University of Portsmouth (GB)
Publication Details
- Journal
- BMC Medical Informatics and Decision Making
- Published
- 2025-08-14
- DOI
- https://doi.org/10.1186/s12911-025-03140-2
- Primary Topic
- Retinal and Macular Surgery
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Natural Science Foundation of Tianjin City