Explores machine learning to detect cardiovascular diseases and diabetes in fingernails, suggesting a novel diagnostic approach.
Disease-related spectral regions attributed to glycated products were captured through near-infrared spectroscopy and when paired with machine learning classification models, produced high levels of predictive accuracy.
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Wilson et al. (2026) studied this question.
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