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Fig. 6 | BioData Mining

Fig. 6

From: Machine-learning-based models to predict cardiovascular risk using oculomics and clinic variables in KNHANES

Fig. 6

ROC and AUC in the internal validation models used both oculomics and clinic as input variables. a-c, g-h Five cut-off points of AIP and TyG-index in the male subgroup. d-f, i-j Five cut-off points of AIP and TyG-index in the female subgroup. AIP, Atherogenic index of plasma. AUC, Area under curve. ROC, Receiver operating characteristic. TyG-index, Triglyceride-glucose index

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ISSN: 1756-0381