Application of NMR-based metabolomics and machine learning for non-invasive disease screening in dogs.

Front Vet Sci · 2026 · PMC13364687 · PMID 42453966

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highly significantno p-value reported

Null models with permuted class labels performed poorly (ROC AUC = 0.508 ± 0.079; PR AUC = 0.280 ± 0.057; Figures 2d , e ), confirming that classification was highly significant and not due to random chance.

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