Abstract: A graphical user interface, referred to herein as a virtual whiteboard, that provides both: (1) an automatically prioritized display of information related to a particular patient that is tailored to the current user of the system, and (2) a “scratch pad” area in which multiple users of the system may input free-form text and other data for sharing with other users of the system. When each user of the system accesses the virtual whiteboard, the system: (1) automatically prioritizes the patient information based on characteristics of the user and displays the automatically prioritized patient information to that user, and (2) displays the contents of the scratch pad to the user. As a result, the whiteboard displays both information that is tailored to the current user and information that is common to all users (i.e., not tailored to any particular user).

Abstract: A computer system generates an initial set of billing codes based on one or more documents (e.g., clinical notes) representing a patient encounter, such as clinical notes created by a physician. The system expands the initial set of billing codes based on a billing code standard to create an expanded set of billing codes for consideration by the physician. The system provides output representing the expanded billing code set to the physician. The physician selects one or more billing codes from the expanded billing code set for inclusion in a final billing code set for use in a bill for the services provided in the patient encounter.

Abstract: A graphical user interface, referred to herein as a virtual whiteboard, that provides both: (1) an automatically prioritized display of information related to a particular patient that is tailored to the current user of the system, and (2) a “scratch pad” area in which multiple users of the system may input free-form text and other data for sharing with other users of the system. When each user of the system accesses the virtual whiteboard, the system: (1) automatically prioritizes the patient information based on characteristics of the user and displays the automatically prioritized patient information to that user, and (2) displays the contents of the scratch pad to the user. As a result, the whiteboard displays both information that is tailored to the current user and information that is common to all users (i.e., not tailored to any particular user).

Abstract: In a method and a device for the calibration of internal combustion engines, in each fuel injector, at least one actuator element (1) may be activated by an electric signal interacts with at least one injection valve (3) having an injection rate for the supply of fuel to a combustion chamber (5) via injection holes, and in the case of a flow characteristic curve (12, 23, 35) of the fuel flowing through the injection holes deviating from a target characteristic curve (11, 22, 34) in a flow-time diagram, a signal characteristic curve (14a, 27, 42) of the electric signal applied to the actuator element (1) is altered in a voltage-time diagram relative to a target characteristic curve (13, 26, 41) by a controller.

Abstract: A system is provided for training an acoustic model for use in speech recognition. In particular, such a system may be used to perform training based on a spoken audio stream and a non-literal transcript of the spoken audio stream. Such a system may identify text in the non-literal transcript which represents concepts having multiple spoken forms. The system may attempt to identify the actual spoken form in the audio stream which produced the corresponding text in the non-literal transcript, and thereby produce a revised transcript which more accurately represents the spoken audio stream. The revised, and more accurate, transcript may be used to train the acoustic model, thereby producing a better acoustic model than that which would be produced using conventional techniques, which perform training based directly on the original non-literal transcript.

Abstract: In a method and the corresponding apparatus for operating an internal combustion engine with a plurality of cylinders (Z1 to Z4) which are assigned in each case one injection valve (18) for metering in fuel, a control apparatus (25) is provided with in each case one output stage (25a) for actuating the injection valves (18) of the plurality of cylinders. Here, first of all work injection operations (P0 to P4) are determined for a cylinder (CYL_i) with the duration and positioning in relation to the crankshaft rotary angle. Following this, late injection operations (P5), which are required in certain operating modes, for the preceding cylinder (CYL_i?1) in the ignition sequence are arranged in a setpoint crankshaft angular range (SB) in such a way that no temporal overlaps occur between individual work and late injection operations.

Abstract: A dataset is searched using inclusion set criteria to produce an inclusion set and exclusion set criteria to produce an exclusion set. A set of unique content elements is identified from the inclusion set and the exclusion set. Metrics are derived from the inclusion set, exclusion set, and set of unique content elements, such as a measure, for each unique content element, of the absolute value of the difference between the percentage of records in the inclusion set containing the unique content element and the percentage of records in the exclusion set containing the unique content element. The unique content element set may be sorted and displayed in decreasing order of the above-referenced absolute value. The content element set may be filtered. Individual content elements may be excluded from the content set. A predictive model may be generated based on the resulting version of the content element set.

Abstract: An automatic speech recognizer is used to produce a structured document representing the contents of human speech. A best practice is applied to the structured document to produce a conclusion, such as a conclusion that required information is missing from the structured document. Content is inserted into the structured document based on the conclusion, thereby producing a modified document. The inserted content may be obtained by prompting a human user for the content and receiving input representing the content from the human user.

Abstract: Techniques are disclosed for facilitating the process of proofreading draft transcripts of spoken audio streams. In general, proofreading of a draft transcript is facilitated by playing back the corresponding spoken audio stream with an emphasis on those regions in the audio stream that are highly relevant or likely to have been transcribed incorrectly. Regions may be emphasized by, for example, playing them back more slowly than regions that are of low relevance and likely to have been transcribed correctly. Emphasizing those regions of the audio stream that are most important to transcribe correctly and those regions that are most likely to have been transcribed incorrectly increases the likelihood that the proofreader will accurately correct any errors in those regions, thereby improving the overall accuracy of the transcript.

Abstract: A method is provided for displaying images from a reverse view camera system of a motor vehicle on a display, which includes, but is not limited to generating an image of a rearward environment of the motor vehicle with the aid of the reverse view camera system, providing an information system in the motor vehicle, displaying the image of the rearward environment on the display, and displaying a parameter associated with the information system on the display whilst driving.

Abstract: A system is provided for training an acoustic model for use in speech recognition. In particular, such a system may be used to perform training based on a spoken audio stream and a non-literal transcript of the spoken audio stream. Such a system my identify text in the non-literal transcript which represents concepts having multiple spoken forms. The system may attempt to identify the actual spoken form in the audio stream which produced the corresponding text in the non-literal transcript, and thereby produce a revised transcript which more accurately represents the spoken audio stream. The revised, and more accurate, transcript may be used to train the acoustic model, thereby producing a better acoustic model than that which would be produced using conventional techniques, which perform training based directly on the original non-literal transcript.

Abstract: A system is provided for training an acoustic model for use in speech recognition. In particular, such a system may be used to perform training based on a spoken audio stream and a non-literal transcript of the spoken audio stream. Such a system may identify text in the non-literal transcript which represents concepts having multiple spoken forms. The system may attempt to identify the actual spoken form in the audio stream which produced the corresponding text in the non-literal transcript, and thereby produce a revised transcript which more accurately represents the spoken audio stream. The revised, and more accurate, transcript may be used to train the acoustic model using discriminative training techniques, thereby producing a better acoustic model than that which would be produced using conventional techniques, which perform training based directly on the original non-literal transcript.

Abstract: An error detection and correction system extracts editing patterns and derives correction rules from them by observing differences between draft documents and corresponding edited documents, and/or by observing editing operations performed on the draft documents to produce the edited documents. The system develops classifiers that partition the space of all possible contexts into equivalence classes and assigns one or more correction rules to each such class). Once the system has been trained, it may be used to detect and (optionally) correct errors in new draft documents. When presented with a draft document, the system identifies first content (e.g., text) in the draft document and identifies a context of the first content. The system identifies a correction rule based on the first content and the first context. The system may use a classifier to identify the correction rule. The system applies the correction rule to the first content to produce second content.

Abstract: A system includes a data record (such as an Electronic Medical Record (EMR)) and a user interface for modifying (e.g., storing data in) the data record. The data record includes both free-form text elements and discrete data elements. The user interface includes user interface elements for receiving free-form text data. In response to receiving free-form text data via the free-form text user interface elements, a suggested action is identified, such as a suggested action to take in connection with one of the discrete data elements of the data record. Output is generated representing the suggested action. A user provides input indicating acceptance or rejection of the suggested action. The suggested action may be performed in response to the user input.

Abstract: Embodiments of the present invention are directed to computer systems for implementing dynamic, data-driven workflows within healthcare and other environments. Such a system may include a computer-processable definition of one or more workflows. Each workflow definition may define various aspects of the corresponding workflow, such as the data required by the workflow, a process for extracting such data from a variety of structured and/or unstructured data sources, a set of process steps to be performed within the workflow, and a condition for triggering the workflow. The system may use the workflow definition to extract the data required by the workflow and to perform the workflow's process steps on the extracted data in response to determining that the workflow's trigger condition has been satisfied. The workflow may change in response to changes in data extracted by the workflow.

Abstract: Techniques are disclosed for automatically generating structured documents based on speech, including identification of relevant concepts and their interpretation. In one embodiment, a structured document generator uses an integrated process to generate a structured textual document (such as a structured textual medical report) based on a spoken audio stream. The spoken audio stream may be recognized using a language model which includes a plurality of sub-models arranged in a hierarchical structure. Each of the sub-models may correspond to a concept that is expected to appear in the spoken audio stream. Different portions of the spoken audio stream may be recognized using different sub-models. The resulting structured textual document may have a hierarchical structure that corresponds to the hierarchical structure of the language sub-models that were used to generate the structured textual document.

Abstract: In a method for determining a vibration-optimised adjustment of an injection device of an internal combustion engine, for each cycle of the internal combustion engine, a plurality of individual injections per cylinder is carried out by the injection device, each of which is defined by a relative injection moment and an individual injection quantity. A temporal course of a resulting pressure influenced by pressure waves is determined in a fuel guiding part, and the above-mentioned adjustment is determined by variation of the injection moment of at least one individual injection and/or the individual quantity, such that the adjustment is characterized by a temporal variation of the resulting pressure, which is reduced by an at least partially destructive interference between the cited pressure waves. A corresponding device can determine a vibration-optimised adjustment of an injection device, and an internal combustion engine may have such a device.

Abstract: A system is provided for training an acoustic model for use in speech recognition. In particular, such a system may be used to perform training based on a spoken audio stream and a non-literal transcript of the spoken audio stream. Such a system may identify text in the non-literal transcript which represents concepts having multiple spoken forms. The system may attempt to identify the actual spoken form in the audio stream which produced the corresponding text in the non-literal transcript, and thereby produce a revised transcript which more accurately represents the spoken audio stream. The revised, and more accurate, transcript may be used to train the acoustic model using discriminative training techniques, thereby producing a better acoustic model than that which would be produced using conventional techniques, which perform training based directly on the original non-literal transcript.

Abstract: An automatic speech recognizer is used to produce a structured document representing the contents of human speech. A best practice is applied to the structured document to produce a conclusion, such as a conclusion that required information is missing from the structured document. Content is inserted into the structured document based on the conclusion, thereby producing a modified document. The inserted content may be obtained by prompting a human user for the content and receiving input representing the content from the human user.

Abstract: A system is provided for training an acoustic model for use in speech recognition. In particular, such a system may be used to perform training based on a spoken audio stream and a non-literal transcript of the spoken audio stream. Such a system may identify text in the non-literal transcript which represents concepts having multiple spoken forms. The system may attempt to identify the actual spoken form in the audio stream which produced the corresponding text in the non-literal transcript, and thereby produce a revised transcript which more accurately represents the spoken audio stream. The revised, and more accurate, transcript may be used to train the acoustic model, thereby producing a better acoustic model than that which would be produced using conventional techniques, which perform training based directly on the original non-literal transcript.