Figure 7 | Scientific Reports

Figure 7

From: Identification of SLC40A1, LCN2, CREB5, and SLC7A11 as ferroptosis-related biomarkers in alopecia areata through machine learning

Figure 7

Nomogram for Predicting the Risk of Alopecia Areata (AA). (a) A nomogram developed using the GSE68801 dataset, incorporating selected marker genes for AA diagnosis. Each gene contributes a score, with the total score indicating the AA risk level. (b) Calibration curve assessing the nomogram's accuracy, where a line closer to the ideal line represents higher predictive accuracy for AA. (c) Receiver Operating Characteristic (ROC) curve for the AA diagnosis using marker genes from the GSE68801 dataset, exhibiting an area under the curve (AUC) of 0.9052, indicating high diagnostic performance. AA, alopecia areata; ROC, receiver operating characteristic; AUC, area under the curve.

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