Effective automatic classification methods via deep learning for myopic maculopathy
The ensemble deep learning system significantly enhances the accuracy and reliability of MM classification. This system holds potential for assisting ophthalmologists in early detection and precise diagnosis, thereby improving patient outcomes. Future work could focus on expanding the dataset, incorporating image quality assessment, and optimizing the ensemble algorithm for better efficiency and broader applicability.
Authors
- Yantao Wei (ORCID: https://orcid.org/0000-0001-7225-1958)
- Wangting Li (ORCID: https://orcid.org/0000-0001-7070-5768)
- Chen Lü (ORCID: https://orcid.org/0000-0003-1927-2391)
- Fang Dong (ORCID: https://orcid.org/0000-0003-3205-9931)
- Zheming Zhang
- Qi Gao (ORCID: https://orcid.org/0009-0002-2106-8445)
- Alfira Mijit
Institutions
- Sun Yat-sen University (CN)
- Jinan University (CN)
- South China University of Technology (CN)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2024-11-13
- DOI
- https://doi.org/10.3389/fmed.2024.1492808
- Citations
- 3
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 1.21