Fig. 7: Reclassification performance achieved by the multiomics models on the combined test set (n = 658). | Nature Communications

Fig. 7: Reclassification performance achieved by the multiomics models on the combined test set (n = 658).

From: Integrated multiomics signatures to optimize the accurate diagnosis of lung cancer

Fig. 7: Reclassification performance achieved by the multiomics models on the combined test set (n = 658).The alternative text for this image may have been generated using AI.

A Confusion matrices illustrating the predicted outcomes generated by the multiomics model in comparison with the actual outcomes, as well as between the multiomics model and the clinical model B the DL-radiomics model C the 6bp-5mC model D the clinic-Radiomics model E and the clinic-mC model F with emphasis placed on the patients ruled in and ruled out. The dotted lines demarcate the corresponding cutoff values of the different models. The number labeled with * refer to cancer cases misclassified as low-risk samples by the x-axis model but correctly reclassified as high-risk samples by the multiomics model on y-axis, whereas the number labeled with # refer to benign cases misclassified as high-risk samples by the x-axis model but correctly reclassified as low-risk samples by the multiomics model on the y-axis. Source data are provided as a Source Data file.

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