Open access
Sep 2026
Cardiovascular Disease Risk Assessment from Retinal Fundus Images Using a CSP-ConvNext Model
The results demonstrate that the CSP-ConvNeXt framework, combining CSP-based feature extraction, ESE attention, large-kernel depthwise convolutions, and hierarchical representation learning, can effectively capture retinal vascular and anatomical patterns associated with cardiovascular risk.
Dhayanithi Jaganathan, Sathiyabhama Balasubramaniam, H. T et al.
· Diagnostics · 0 citations