Neurosymbolic AI Framework for Explainable Retinal Disease Classification From OCT Images
By integrating symbolic clinical logic with visual pattern recognition, the neurosymbolic model fosters trust in artificial intelligence-assisted diagnostics and supports precise, explainable decision-making in retinal care.
Authors
- Leandro Inferrera (ORCID: https://orcid.org/0000-0003-2854-4141)
- Simone Kresevic (ORCID: https://orcid.org/0009-0008-1700-7512)
- Daniele Tognetto (ORCID: https://orcid.org/0000-0001-7197-7765)
- Agostino Accardo (ORCID: https://orcid.org/0000-0001-5749-6308)
- Aleksandar Miladinović (ORCID: https://orcid.org/0000-0002-6156-1464)
- Miloš Ajčević (ORCID: https://orcid.org/0000-0001-8307-4360)
- Alessandro Biscontin (ORCID: https://orcid.org/0009-0006-7918-7438)
Institutions
- University of Trieste (IT)
- IRCCS Materno Infantile Burlo Garofolo (IT)
Publication Details
- Journal
- Translational Vision Science & Technology
- Published
- 2026-01-06
- DOI
- https://doi.org/10.1167/tvst.15.1.6
- Citations
- 1
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 31.92