Abstract: Techniques for processing a user input are described. Text data representing a user input is processed with respect to at least one finite state transducer (FST) to generate at least one FST hypothesis. Context information may be required to traverse one or more paths of the at least one FST. The text data is also processed using at least one statistical model (e.g., perform intent classification, named entity recognition, and/or domain classification processing) to generate at least one statistical model hypothesis. The at least one FST hypothesis and the at least one statistical model hypothesis are input to a reranker that determines a most likely interpretation of the user input.

Abstract: A system that can be used for targeted radiology resident training can include a memory storing computer-executable instructions and a processor to access the memory and execute the computer-executable instructions to at least receive a preliminary report and a corresponding final report; determine a difference between the final radiology report and the preliminary radiology report; classify the difference as substantive or stylistic based on a property of the difference; and produce an output including the difference when classified as substantive. The output can include one or more critical errors reflected in the substantive difference. The one or more critical errors can be used to facilitate radiology resident training.