Abstract: A patient information interface system presents an aggregated, graphical view of patient anatomy and history. The system includes a graphical representation of at least a portion of a human anatomy including one or more indicators, aggregated from a plurality of clinical information sources and located at anatomical locations on the representation, that correspond to clinical events that have occurred in connection with a patient. The system also includes an electronic health record timeline of clinical events for the patient. The timeline includes the same one or more indicators that are displayed on the graphical representation corresponding to clinical events that have occurred in connection with a patient. A selection or change of an indicator on one of the graphical representation or the electronic health record timeline triggers a corresponding selection or change of the indicator on the other of the graphical representation or the electronic health record timeline.

Abstract: A patient information interface system presents an aggregated, graphical view of patient anatomy and history. The system includes a graphical representation of at least a portion of a human anatomy including one or more indicators, aggregated from a plurality of clinical information sources and located at anatomical locations on the representation, that correspond to clinical events that have occurred in connection with a patient. The system also includes an electronic health record timeline of clinical events for the patient. The timeline includes the same one or more indicators that are displayed on the graphical representation corresponding to clinical events that have occurred in connection with a patient. A selection or change of an indicator on one of the graphical representation or the electronic health record timeline triggers a corresponding selection or change of the indicator on the other of the graphical representation or the electronic health record timeline.

Abstract: Systems and methods for promoting personal health are provided. Sponsors of a health-related challenge program such as employees can set up goals, select participants, select duration and select prizes or rewards for the participants. The sponsors may also specify one or more acceptable user devices or tracking services that may be used by the participants of the program. The challenge programs may be individual or team based. Users of the present invention can enroll in the programs in any suitable fashion such as through a web interface and/or a health kiosk. A user may activate the enrollment at a health kiosk. The user may associate and/or dissociate tracking devices and/or services with a user account. Data collected at the health kiosk and/or from the associated tracking devices or services may be used to determine the performance of users or groups of users in the challenge programs.

Abstract: Certain embodiments present a system for generating a medical teaching file message. An image identifier labels medical images based upon information pertaining to user interaction with the image. The system also provides an image search engine that scans and indexes images within a database based on a set of rules. The image search engine generates a subset of images from a larger group of medical images within a database based upon the rules. The system also includes a supporting data selection engine for accepting a free text search query from an interface. The supporting data selection engine scans medical databases based on the free text search query, and provides the supporting data search results via an interface. A teaching file message is generated either automatically or manually from the subset of images and the supporting data search results for transmission to a teaching file.

Abstract: Techniques for automatically detecting meniscus include receiving pixels from a scanning device directed to a knee of a subject. Also received is a region of interest that includes pixels that correspond to at least a portion of a meniscus of the knee. Without human intervention, a meniscus extraction threshold is determined based on pixel intensities in the region of interest. A meniscus object portion of the scan data is further determined without human intervention based on the meniscus extraction threshold and a geometrical constraint. Other techniques for automatically detecting meniscal tears includes receiving a meniscus object portion of scan data from a scanning device and receiving threshold data that indicates a meniscus extraction threshold. Without human intervention, a propensity for meniscal tears is determined based on the threshold data and the meniscus object portion of the scan data.

Abstract: A patient information interface system presents an aggregated, graphical view of patient anatomy and history. The system includes a graphical representation of at least a portion of a human anatomy including one or more indicators, aggregated from a plurality of clinical information sources and located at anatomical locations on the representation, that correspond to clinical events that have occurred in connection with a patient. The system also includes an electronic health record timeline of clinical events for the patient. The timeline includes the same one or more indicators that are displayed on the graphical representation corresponding to clinical events that have occurred in connection with a patient. A selection or change of an indicator on one of the graphical representation or the electronic health record timeline triggers a corresponding selection or change of the indicator on the other of the graphical representation or the electronic health record timeline.

Abstract: Certain embodiments present a system for generating a medical teaching file message. An image identifier labels medical images based upon information pertaining to user interaction with the image. The system also provides an image search engine that scans and indexes images within a database based on a set of rules. The image search engine generates a subset of images from a larger group of medical images within a database based upon the rules. The system also includes a supporting data selection engine for accepting a free text search query from an interface. The supporting data selection engine scans medical databases based on the free text search query, and provides the supporting data search results via an interface. A teaching file message is generated either automatically or manually from the subset of images and the supporting data search results for transmission to a teaching file.

Abstract: Techniques for automatically detecting meniscus include receiving pixels from a scanning device directed to a knee of a subject. Also received is a region of interest that includes pixels that correspond to at least a portion of a meniscus of the knee. Without human intervention, a meniscus extraction threshold is determined based on pixel intensities in the region of interest. A meniscus object portion of the scan data is further determined without human intervention based on the meniscus extraction threshold and a geometrical constraint. Other techniques for automatically detecting meniscal tears includes receiving a meniscus object portion of scan data from a scanning device and receiving threshold data that indicates a meniscus extraction threshold. Without human intervention, a propensity for meniscal tears is determined based on the threshold data and the meniscus object portion of the scan data.