Fig. 4From: Clinico-biological-radiomics (CBR) based machine learning for improving the diagnostic accuracy of FDG-PET false-positive lymph nodes in lung cancerReceiver-operating characteristic analysis of models for predicting LNs status in the training set (a) and (b), respectively. Decision curve analysis of prediction models in the training set (c). The X-axis represented the threshold probability that was where the expected benefit of treatment was equal to the expected benefit of avoiding treatment. The Y-axis represented the net benefit. The grey and black line represented the hypothesis that all lung cancer patients were LN + and LN−, respectivelyBack to article page