Deep-Learning-Assisted Analysis of Early Biomarker Changes in Treatment-Naïve Patients with Neovascular AMD Under Intravitreal Faricimab
This study demonstrates the potential of AI-assisted biomarker analysis for precise disease monitoring in nAMD. Faricimab significantly reduced disease activity biomarkers and improved visual acuity in treatment-naïve patients, reinforcing its efficacy in early disease control. Future studies should explore long-term outcomes and further integrate AI-driven biomarker evaluation in clinical practice.
Authors
- Ben Asani (ORCID: https://orcid.org/0000-0003-4809-2859)
- Jakob Siedlecki (ORCID: https://orcid.org/0000-0002-0279-4823)
- Michael Hafner
- Benedikt Schworm (ORCID: https://orcid.org/0000-0003-0753-2408)
- Johannes Schiefelbein (ORCID: https://orcid.org/0000-0001-5357-7469)
- Franziska Eckardt (ORCID: https://orcid.org/0000-0001-5883-2529)
- Siegfried Priglinger
Institutions
- LMU Klinikum (DE)
- Ludwig-Maximilians-Universität München (DE)
Publication Details
- Journal
- Ophthalmology and Therapy
- Published
- 2025-03-25
- DOI
- https://doi.org/10.1007/s40123-025-01125-y
- Citations
- 2
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 2.72
Funders
- Bundesministerium für Bildung und Forschung
- Helmholtz Association