Fig. 4

Machine learning results for the time-resolved networks. a) Performance metrics for the test-set (future) indications across the different network years. Only drugs approved after the year of the network are included in the test-set, while those approved prior are used for training. b) Box plots of the values of the model coefficients across all of the different network years. The top-10 coefficients with largest mean value across all models are shown. c) Probabilities of treatment of selected indications for each network model containing both the Drug and Disease concepts. Arrows indicate the year that the drug was first approved for any indication. Points left of the arrow on the graph, the indication was used as part of the validation set, and those to the right, the training set. d) AUROC and AUPRC data for indications based on their probabilities, split by the number of years between drug approval date and the year of the network. Values to the left of the Zero Point are indications approved before the network year thus part of the training-set, while those to the right are part of the test-set. Probabilities for all drug-disease pairs were standardized before combining across models. Points are given for each data point, while lines represent a 5-year rolling average of metrics