AI Article Synopsis
- Scientists created a smart computer program called UWF-CKDS to help find out if someone has chronic kidney disease (CKD) using special images of the eyes.
- They tested this program with information from 23 hospitals in China and found that it worked really well.
- The program looks at tiny details in the eye that relate to kidney health, making it better than older methods at predicting CKD for many people.
Article Abstract
To address challenges in screening for chronic kidney disease (CKD), we devised a deep learning-based CKD screening model named UWF-CKDS. It utilizes ultra-wide-field (UWF) fundus images to predict the presence of CKD. We validated the model with data from 23 tertiary hospitals across China. Retinal vessels and retinal microvascular parameters (RMPs) were extracted to enhance model interpretability, which revealed a significant correlation between renal function and RMPs. UWF-CKDS, utilizing UWF images, RMPs, and relevant medical history, can accurately determine CKD status. Importantly, UWF-CKDS exhibited superior performance compared to CTR-CKDS, a model developed using the central region (CTR) cropped from UWF images, underscoring the contribution of the peripheral retina in predicting renal function. The study presents UWF-CKDS as a highly implementable method for large-scale and accurate CKD screening at the population level.
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Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11458603 | PMC |
| http://dx.doi.org/10.1038/s41746-024-01271-w | DOI Listing |
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