Abstract: A set of user interface tools is described facilitating asynchronous adjudication of one or more regions-of-interest in a medical image by a group of two or more graders, each of which has access to the set of tools in a workstation environment. The set of tools include (1) a feature for enabling the graders to assess the medical image and manually delineate one or more specific regions-of-interest (ROI) in the medical image, (2) a feature for assessing the ROI(s) delineated by other graders, including display of the ROI delineated by other graders; (3) dialog features for explaining and discussing the assessments, including a text feature for discussing the assessments. The dialog features and the ROIs delineated by all the graders are visible to all the graders on the workstation display as they collectively adjudicate the medical image in a round-robin manner. The set of tools further include (4) a feature for manually verifying grader agreement with the other graders' assessments.

Abstract: A computer-implemented method includes displaying a number of questions on a stack of overlapping graphical objects that dynamically indicates a status of the number of remaining questions, determining an output based on answers input by a user, and displaying an indication of the output.

Abstract: A set of user interface tools is described facilitating asynchronous adjudication of one or more regions-of-interest in a medical image by a group of two or more graders, each of which has access to the set of tools in a workstation environment. The set of tools include (1) a feature for enabling the graders to assess the medical image and manually delineate one or more specific regions-of-interest (ROI) in the medical image, (2) a feature for assessing the ROI(s) delineated by other graders, including display of the ROI delineated by other graders; (3) dialog features for explaining and discussing the assessments, including a text feature for discussing the assessments. The dialog features and the ROIs delineated by all the graders are visible to all the graders on the workstation display as they collectively adjudicate the medical image in a round-robin manner. The set of tools further include (4) a feature for manually verifying grader agreement with the other graders' assessments.

Abstract: A system obtains patient data, de-identifies each patient with a unique patient key (UPK) and joins the patient data without linking to personal identities of the patients. The system further receives a search query from a user device, identifies a group of UPKs associated with patient data that satisfies criteria of the search query based on values for associated healthcare attributes, and clusters the group of UPKs with respect to healthcare events. The system then ranks the healthcare events of the clusters and sends a query result including healthcare data that is generated based on the ranking, where the query result conceals any personal identity of any of the patients.

Abstract: A computer-implemented method includes displaying a number of questions on a stack of overlapping graphical objects that dynamically indicates a status of the number of remaining questions, determining an output based on answers input by a user, and displaying an indication of the output.

Abstract: Disclosed are systems and techniques for providing a master health entity index and a data analysis mechanism designed for entity cohort discovery and entity profiling. The entity can be a healthcare facility that diagnoses or treats health conditions and diseases (e.g., hospital, clinic), individuals (e.g., providers, patients, caregivers), healthcare data (e.g., medical conditions, treatments, diagnostic studies, health outcomes), etc. For example, a data analysis mechanism may identify distinctive patient cohorts based on what happened to patients in a hospital and why the occurrence happened, glean insight from the activities of the distinctive patient cohorts, and assist with additional patients with the gleaned insight.

Abstract: Introduced are methods and systems for gathering information from a healthcare consumer using context-based questions, and progressively presenting information associated with a ranked list of suggested healthcare providers. First, the server gathers information associated with the healthcare consumer using context-based questions. Each question is formulated based on the answers the healthcare consumer has provided to previous questions, so that minimal and necessary questions are asked. Second, the server progressively sends to a healthcare consumer device, information associated with a ranked list of suggested healthcare providers. The first information tier sent to the healthcare consumer device includes a graphic representing the match strength between the healthcare consumer and the healthcare provider, and the number of similar healthcare consumers the healthcare provider has treated. Based on the healthcare consumer interest, the server displays additional information to the healthcare consumer.

Abstract: A method includes: presenting, on a device, a view of at least part of an augmented reality (AR) environment, the AR environment including a first AR location corresponding to a first physical location in a physical environment; initiating a download to the device of first data representing a first AR object associated with the first AR location; assigning a size parameter to a first loading indicator for the first AR object based on a size of the first AR object; determining a spatial relationship between the view and the first physical location; and presenting the first loading indicator in the view, the first loading indicator having a size based on the assigned size parameter and being presented at a second AR location based on the determined spatial relationship.

Abstract: A method includes: presenting, on a device, a view of at least part of an augmented reality (AR) environment, the AR environment including a first AR location corresponding to a first physical location in a physical environment; initiating a download to the device of first data representing a first AR object associated with the first AR location; assigning a size parameter to a first loading indicator for the first AR object based on a size of the first AR object; determining a spatial relationship between the view and the first physical location; and presenting the first loading indicator in the view, the first loading indicator having a size based on the assigned size parameter and being presented at a second AR location based on the determined spatial relationship.

Abstract: Disclosed are methods and systems for identifying and profiling focus areas of healthcare providers. Embodiments include technology that identifies focus areas automatically from healthcare information such as diagnoses and procedures. As such, healthcare providers that frequently diagnose and/or treat patients for similar conditions may be automatically grouped into the same cluster. Expert knowledge may then be used to label a cluster as a focus area.

Abstract: Introduced are methods and systems for gathering information from a healthcare consumer using context-based questions, and progressively presenting information associated with a ranked list of suggested healthcare providers. First, the server gathers information associated with the healthcare consumer using context-based questions. Each question is formulated based on the answers the healthcare consumer has provided to previous questions, so that minimal and necessary questions are asked. Second, the server progressively sends to a healthcare consumer device, information associated with a ranked list of suggested healthcare providers. The first information tier sent to the healthcare consumer device includes a graphic representing the match strength between the healthcare consumer and the healthcare provider, and the number of similar healthcare consumers the healthcare provider has treated. Based on the healthcare consumer interest, the server displays additional information to the healthcare consumer.

Abstract: Disclosed are systems and techniques for providing a master health entity index and a data analysis mechanism designed for entity cohort discovery and entity profiling. The entity can be a healthcare facility that diagnoses or treats health conditions and diseases (e.g., hospital, clinic), individuals (e.g., providers, patients, caregivers), healthcare data (e.g., medical conditions, treatments, diagnostic studies, health outcomes), etc. For example, a data analysis mechanism may identify distinctive patient cohorts based on what happened to patients in a hospital and why the occurrence happened, glean insight from the activities of the distinctive patient cohorts, and assist with additional patients with the gleaned insight. .