Abstract:
This disclosure describes systems, devices, and techniques for identifying sections of medical documents that are suitable for automated medical coding. In one example, a computer-implemented method includes receiving, by one or more processors, the medical document, wherein the medical document comprises a plurality of sections. The method also may include determining, by the one or more processors and via application of a classification model to each section of the plurality of sections, codability indicia for each section of the plurality of sections, wherein the codability indicia represents whether the respective section is suitable for automated medical coding. The method may include outputting, by the one or more processors, the respective codability indicia for each section of the plurality of sections.
Abstract:
At least some embodiments of the present disclosure feature systems and methods for assessing the impact of visual features within a region of a scene. With the input of a visual representation of a scene and at least one selected region within the scene, the system applies a visual attention model to the visual representation to determine visual conspicuity of the at least one selected region. The system computes feature-related data associated with a plurality of features of the at least one selected region. Based on the visual conspicuity and the feature-related data, the system assesses an impact that at least one of the features within the at least one selected region have on the visual conspicuity.