Session-by-Session Prediction of Anti-Endothelial Growth Factor Injection Needs in Neovascular Age-Related Macular Degeneration Using Optical-Coherence-Tomography-Derived Features and Machine Learning
These findings suggest that session-by-session prediction of injection needs in nAMD patients is feasible, even without processing the entire OCT image. The proposed ML framework has the potential to be integrated into routine clinical workflows, thereby optimizing nAMD therapeutic management.
Authors
- Diego Sona (ORCID: https://orcid.org/0000-0003-2883-5336)
- Francesco Nasini (ORCID: https://orcid.org/0000-0001-7618-7308)
- Chiara Vivarelli (ORCID: https://orcid.org/0009-0004-5139-254X)
- Ginevra Giovanna Adamo
- Stefano Bovo (ORCID: https://orcid.org/0000-0002-0278-6786)
- Flavio Ragni (ORCID: https://orcid.org/0000-0001-7767-7288)
- Marco Mura (ORCID: https://orcid.org/0000-0001-5283-5366)
- Francesco Parmeggiani (ORCID: https://orcid.org/0000-0002-9296-0986)
- Katia De Nadai
- Marco Pellegrini (ORCID: https://orcid.org/0000-0002-3550-591X)
- Giuseppe Jurman (ORCID: https://orcid.org/0000-0002-2705-5728)
- Marco Tavolato
- Andrea Zen
Institutions
- University of Ferrara (IT)
- Fondazione Bruno Kessler (IT)
- King Khaled Eye Specialist Hospital (SA)
- Arcispedale Sant'Anna (IT)
- Regione del Veneto (IT)
Publication Details
- Journal
- Diagnostics
- Published
- 2024-11-21
- DOI
- https://doi.org/10.3390/diagnostics14232609
- Citations
- 2
- Primary Topic
- Retinal Diseases and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 1.08
Funders
- Ministero della Salute