Predicts new uses for existing compounds. Project Rephetio Browser uses machine learning to systematically learn network patterns of drug efficacy. This method translates the network paths between a compound and disease into a predicted probability of treatment. It makes predictions for 1538 approved small molecule compounds and 136 complex diseases, resulting in a total of 209168 compound-disease pairs. Predictions are created from Hetionet v1.0, an integrative network of biomedicine that contains 2250197 relationships of 24 types. Data about compounds (identifiers, names, and desciptions) are from DrugBank, while diseases are from the Disease Ontology.