Vision transformer based interpretable metabolic syndrome classification using retinal Images
Abstract Metabolic syndrome is leading to an increased risk of diabetes and cardiovascular disease. Our study developed a model using retinal image data from fundus photographs taken during comprehensive health check-ups to classify metabolic syndrome. The model achieved an AUC of 0.7752 (95% CI: 0....
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
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| Series: | npj Digital Medicine |
| Online Access: | https://doi.org/10.1038/s41746-025-01588-0 |
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