Fig. 3From: Clinico-biological-radiomics (CBR) based machine learning for improving the diagnostic accuracy of FDG-PET false-positive lymph nodes in lung cancerViolin plot of 6 prediction models for LN− (blue) and LN + (red) patients in training set (a). The black line running up and down through the violin diagram represented the range from the smallest non-outlier value to the largest non-outlier value. The waterfall plot of the CBR Model was used to visualize the distribution of the Pre-scores of individual LN− and LN + patients (b)Back to article page