Abstract: Techniques for analyzing patient health records are provided. Clinical documents may be received in response to a patient-initiated request, for example. In one embodiment, machine learning algorithms are used to sectionalize and extract data from clinical documents. The machine learning algorithms used may be more highly focused for analyzing text residing deeper in a clinical document hierarchy, for example. In one embodiment, extracted data is stored in a patient graph. Searches may be made against the graph to yield results to help save lives and/or improve patient outcomes.

Abstract: Techniques for analyzing patient health records are provided. Clinical documents may be received in response to a patient-initiated request, for example. In one embodiment, machine learning algorithms are used to sectionalize and extract data from clinical documents. The machine learning algorithms used may be more highly focused for analyzing text residing deeper in a clinical document hierarchy, for example. In one embodiment, extracted data is stored in a patient graph. Searches may be made against the graph to yield results to help save lives and/or improve patient outcomes.

Abstract: A method and system for capturing digital data directly from an electronic device's port and processing the data into extensible markup language (XML) form. The integration appliance is configured with desired templates and XML output destination information. A port driver captures the data flowing through the port on its way to the printer. The data is scanned and the data format is determined. The data is parsed into fields and data. The parsed data is scanned to determine the correct template to apply. The correct template is applied to the data to pull out fields and corresponding data. The fields and corresponding data is transformed to XML output. This XML output is sent to a predefined destination.