Abstract: A system includes first, second and third input data sets. The first input data set includes demographic information characterizing a patient. The second and third input data sets characterize a healthcare treatment history of the patient. A neural network includes first, second and third neural subnetworks. The first neural subnetwork is configured to process the first input data set to produce a first output data set. The second neural subnetwork is configured to process the second input data set to produce a second output data set. The third neural subnetwork is configured to process the third input data set to produce a third output data set. An autoencoder layer has an input layer comprising the first, second and third output data sets and is configured to process the first, second and third output data sets to produce a secondary output data set.

Abstract: A unified framework for healthcare workflows to introduce multiple integrated approaches to error analysis. A first approach uses machine learning to extend probabilistic record linkage and apply it to the task of reconciliation, classifying changes between datasets as intentional or unintentional. A second approach uses process mining to extract maximum information about process diagrams and process bottlenecks.

Abstract: The current application is directed to methods and systems for translation of medical codes, including translation of codewords from one medical-concept code to another. The method and systems to which the current application is directed employ a multi-step translation process to translate a source codeword to a corresponding target codeword, associating the source codeword with underlying medical concepts which are, in turn, used to identify candidate target codewords of another medical-concept code. A variety of different weighting-based and filter-like criteria are then employed to select a target codeword from the candidate target codeword. The methods and systems to which the current application is directed provide for more accurate and reliable translations than would be obtained using naive, simple table-based translation.