PMPred-AE: a computational model for the detection and interpretation of pathological myopia based on artificial intelligence
The developed PMPred-AE model is capable of reliably providing accurate PM detection. In addition, the Grad-CAM technology was also used to provide an intuitive and visual interpretation for the decision-making process of the model. This approach provides healthcare professionals with an effective tool for interpretable AI decision-making process.
Authors
- Maha A. Thafar (ORCID: https://orcid.org/0000-0003-0539-7361)
- Peiling Cai (ORCID: https://orcid.org/0000-0003-2748-9734)
- Hao Lin (ORCID: https://orcid.org/0000-0001-6265-2862)
- Hua Tang (ORCID: https://orcid.org/0000-0001-6728-4544)
- Somayah Albaradei
- Shuicheng Yan (ORCID: https://orcid.org/0000-0001-8906-3777)
- Muhammad Arif (ORCID: https://orcid.org/0000-0002-6355-6204)
- Hongqi Zhang (ORCID: https://orcid.org/0000-0001-8740-6828)
Institutions
- University of Electronic Science and Technology of China (CN)
- Taif University (SA)
- King Abdulaziz University (SA)
- Southwest Medical University (CN)
- Chengdu University (CN)
- Hamad bin Khalifa University (QA)
- Chengdu University of Traditional Chinese Medicine (CN)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2025-03-13
- DOI
- https://doi.org/10.3389/fmed.2025.1529335
- Citations
- 26
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 35.36
Funders
- National Natural Science Foundation of China