Overview of methods and results. For each of the 2 362 950 possible drug–disorder pairs, we calculated 9 features from the free text of clinical notes in STRIDE, 8 features from known AEs in Medi-Span, and 12 features from known usages in Medi-Span and Drugbank. Based on these features, a Random Forest classifier was trained on the gold standard dataset to recognize the drug–AE relationships. Then, we applied the trained classifiers to the 2 362 950 possible drug–disorder pairs and filtered for support in FAERS and MEDLINE, yielding a set of 240 well supported, high confidence ADEs. Drug–AE pairs used in training are censored.