Fundus Image Deep Learning Study to Explore the Association of Retinal Morphology with Age-Related Macular Degeneration Polygenic Risk Score
The findings indicate an association between fundus images and AMD PRS, suggesting that deep learning models may effectively estimate genetic risk for AMD from retinal images, potentially aiding in early detection and personalized treatment strategies.
Authors
- Edward Wylęgała (ORCID: https://orcid.org/0000-0002-6707-5790)
- Andrzej W. Mitas (ORCID: https://orcid.org/0000-0001-7833-5845)
- Adam Sendecki (ORCID: https://orcid.org/0000-0001-7605-8653)
- Julia Nycz (ORCID: https://orcid.org/0000-0001-6031-1423)
- Anna Boguszewska‐Chachulska (ORCID: https://orcid.org/0009-0004-5421-8678)
- Sławomir Teper (ORCID: https://orcid.org/0000-0002-0935-8880)
- Daniel Ledwoń (ORCID: https://orcid.org/0000-0001-7704-2901)
- Anna Wąsowska (ORCID: https://orcid.org/0000-0003-0913-4497)
- Aleksandra Tuszy (ORCID: https://orcid.org/0009-0005-1334-0236)
Institutions
- Silesian University of Technology (PL)
- Technische Universität Ilmenau (DE)
- Medical University of Silesia (PL)
- Polish-Japanese Academy of Information Technology (PL)
- Institute of Medical Technology and Equipment (PL)
- Genomed (Poland) (PL)
Publication Details
- Journal
- Biomedicines
- Published
- 2024-09-13
- DOI
- https://doi.org/10.3390/biomedicines12092092
- Citations
- 1
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.40
Funders
- Silesian University of Technology
- Uniwersytet Śląski w Katowicach
- Narodowe Centrum Badań i Rozwoju