Figure 4.

Development and blind test of serum metabolic fingerprints (SMFs) based tri modal pulmonary nodule classification model. A) Schematic overview of the random forest approach used to develop and validate the SMFs based tri modal pulmonary nodule classification model. B) Receiver operating characteristic curve (ROC) of different machine learning algorithms using ten fold cross‐validation in the training set. C) Scatter plot for the graphical comparison of Image‐AI and MPI‐RF in the whole cohort. D) ROC of pulmonary nodule classification models in the training and test set.