Explainable Neutrosophic Knowledge Distillation Model for Ocular Disease Classification Using Ultra-Wide Field Fundus Images
Nebras Sobahi, Muhammed Halil Akpınar, Salih Taha Alperen Özçelik, Abdulkadir Sengur · 2026
Read Explainable Neutrosophic Knowledge Distillation Model for Ocular Disease Classification Using Ultra-Wide Field Fundus Images by Nebras Sobahi, Muhammed Halil Akpınar, Salih Taha Alperen Özçelik, Abdulkadir Sengur (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13203305.txt.
Description
Sobahi, Akpınar, Özçelik, and Sengur classified eye diseases in this study from twenty twenty-six. Their images are ultra-wide photos of the retina, which are hard to sort because disease classes look alike. Class sizes also skew, and some patterns stay ambiguous. The team built a student model taught by a larger teacher network.
Their twist is a logic that grades truth, falsehood, and uncertainty separately during teaching. An image-cleaning step evens out contrast before training. Heat maps showed the model looked at sensible retinal regions when deciding. Accuracy averaged about eighty-four percent across validation folds. The model beat classic feature-based methods and plainer student networks. The authors offer it as decision support for screening.
Catalog record
| CREATOR | Nebras Sobahi, Muhammed Halil Akpınar, Salih Taha Alperen Özçelik, Abdulkadir Sengur |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 65 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |