Abstract: Disclosed are techniques for predicting, reporting, and preventing medical adverse events, such as septicemia. The techniques may be implemented in a client-server arrangement, where the clients are present on medical professionals' smart phone, for example. The disclosed techniques' ability to detect impending medical adverse events utilizes two innovations. First, some embodiments include a flexible and scalable joint model based upon sparse multiple-output Gaussian processes. Unlike state-of-the-art joint models, the disclosed model can explain highly challenging structure including non-Gaussian noise while scaling to large data. Second, some embodiments utilize an optimal policy for predicting events using the distribution of the event occurrence estimated by the joint model.