FigureĀ 2.
Performance of neural networks NN01 and NN03 for the differentiation between patients with APS and controls treated with VKAs. (A-B) Confusion matrices showing the accuracy of patients with APS classification by NN01 (A) and NN03 (B) in the developmental phase. (C-D) ROC curve of the diagnostic accuracy of NN01 (C) and NN03 (D) to identify patients with APS. (E-F) Quantification of APS suspicion by NN01 (E) and NN03 (F) according to subject type. (G) Quantified sensitivity and specificity of NN01 (blue) and NN03 (green) for the diagnosis of APS. (H) Positive and negative predictive values of NN01 (blue) and NN03 (green) for the diagnosis of APS.

Performance of neural networks NN01 and NN03 for the differentiation between patients with APS and controls treated with VKAs. (A-B) Confusion matrices showing the accuracy of patients with APS classification by NN01 (A) and NN03 (B) in the developmental phase. (C-D) ROC curve of the diagnostic accuracy of NN01 (C) and NN03 (D) to identify patients with APS. (E-F) Quantification of APS suspicion by NN01 (E) and NN03 (F) according to subject type. (G) Quantified sensitivity and specificity of NN01 (blue) and NN03 (green) for the diagnosis of APS. (H) Positive and negative predictive values of NN01 (blue) and NN03 (green) for the diagnosis of APS.

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