1. A computer-implemented method for detection of latent signals in adverse event information, comprising: receiving a set of adverse event information; identifying a first adverse event; identifying a second set of adverse events from the first set of adverse events that are associated with the first adverse event; receiving a training dataset; training a predictive model using the second set of events and the training dataset; and applying the predictive model to a test dataset to determine hidden adverse events.