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Fig. 5 | BMC Bioinformatics

Fig. 5

From: A dropout-regularized classifier development approach optimized for precision medicine test discovery from omics data

Fig. 5

Results are shown for the classifier trained on the problem confounded by tumor histology for differentiation of subjects with NSCLC surviving at least four years post-surgery from those dying before four years. The ROC curves correspond to the case when no additional filtering constraint is applied using data from patients with non-squamous histology with insufficient follow up

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