A Convolutional Neural Network to Identify Parkinson’s Disease using Multimodal Retinal Images
Alexander Richardson, Anita Kundu, Ricardo Henao, Terry Lee, Burton L Scott, Dilraj S Grewal, Sharon Fekrat · 2025
Read A Convolutional Neural Network to Identify Parkinson’s Disease using Multimodal Retinal Images by Alexander Richardson, Anita Kundu, Ricardo Henao, Terry Lee, Burton L Scott, Dilraj S Grewal, Sharon Fekrat (2025) 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-11716891.txt.
Description
Alexander Richardson and co-authors build a 2025 computer model that tries to spot Parkinson's disease from eye images. The back of the eye shares features with the brain, and earlier scans had shown clear differences in people with the disease.
The team trained their network on several kinds of retinal scans from people with Parkinson's and from healthy controls. The best model sorted the two groups with strong accuracy. Wide-field color photos of the retina helped most, while thickness maps helped least. The authors say more images and more varied cases are still needed before such a tool could support doctors in the clinic.
Catalog record
| CREATOR | Alexander Richardson, Anita Kundu, Ricardo Henao, Terry Lee, Burton L Scott, Dilraj S Grewal, Sharon Fekrat |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 3 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |