Abstract: In at least one embodiment, an automated medical data machine learning system and method allow a natural language processing (“NLP”) system to automatically learn via, for example, feedback to improve ongoing performance of the natural language processing system. The particular technology for improving the interpretation by the NLP system of future input data is a matter of design choice. In at least one embodiment, the automated medical data learning system and method includes a linguistics module that determines the part of speech of a particular term or term, such as use as a noun or verb. In at least one embodiment, the system and method learns an interpretation based on a source of the input data. In at least one embodiment, the system and method includes a statistics module that allows the system and method to determine a most probable interpretation or multiple interpretations.

Abstract: In at least one embodiment, a system and method provides a paradigm shift in generating a medical record by allowing a clinician increased flexibility in documenting a patient examination and treatment while still generating a structured medical record that facilitates multiple, subsequent processing options. In at least one embodiment, the system and method utilize natural language processing and feedback to generate a complete, electronic medical record.

Abstract: The present invention provides compositions and methods for increasing absorption of poorly absorbable antibiotics, particularly third generation cephalosporin antibiotics, in oral dosage solid and/or suspension forms. Specifically, the composition is comprised of a biopolymer that is preferably swellable and/or mucoadhesive, a poorly absorbable antibiotic, and a cationic binding agent contained within the biopolymer such that the binding agent is tonically bound or complexed to at least one member selected from the group consisting of the biopolymer and the antibiotic.