Abstract: A system and method prioritizes and presents heterogenous medical data. The method includes retrieving medical data of a patient, the medical data including data from multiple data sources. The method includes phenotyping the medical data to generate a reasoning trail and reasoning outcome including one or more codes, the reasoning trail including a basis for which the reasoning outcome is determined. The method includes assigning a relevance score to each of the one or more codes. The method includes ranking the codes based on the relevance score of each of the one or more codes. The method includes displaying the codes in rank order.

Abstract: A system and/or method that facilitates sharing image viewing context between vendor visualization applications without integration of different software application from different vendors packages is describe herein. In one instance, a visualization computing system (102) includes a processor (116) that executes computer readable instructions that capture a visual context of an imaging study displayed via a basic visualization application running on a vendor computing system, identify the study based on the captured visual context, load the study on the visualization computing system, and launch an advanced visualization application, which allows viewing and manipulation of the loaded study using advanced visualization tools unavailable by the basic visualization application.

Abstract: A system and method prioritizes and presents heterogenous medical data. The method includes retrieving medical data of a patient, the medical data including data from multiple data sources. The method includes phenotyping the medical data to generate a reasoning trail and reasoning outcome including one or more codes, the reasoning trail including a basis for which the reasoning outcome is determined. The method includes assigning a relevance score to each of the one or more codes. The method includes ranking the codes based on the relevance score of each of the one or more codes. The method includes displaying the codes in rank order.

Abstract: An apparatus (10) for assessing radiologist performance includes at least one electronic processor (20) programmed to: during reading sessions in which a user is logged into a user interface (UI) (27), present (98) medical imaging examinations (31) via the UI, receive examination reports on the presented medical imaging examinations via the UI, and file the examination reports; and perform a tracking method (102, 202) including at least one of: (i) computing (204) concurrence scores (34) quantifying concurrence between clinical findings contained in the examination reports and corresponding computer-generated clinical findings for the presented medical imaging examinations which are generated by a computer aided diagnostic (CAD) process miming as a background process during the reading sessions; and/or (ii) determining (208) reading times (38) for the presented medical imaging examinations wherein the reading time for each presented medical imaging examination is the time interval between a start of the prese

Abstract: A patient monitor (8) includes a display (10). Patient values (38) are obtained for one or more known variables of a risk prediction function (30). One or more unknown variables of the risk prediction function are determined, and at least one hyperplane (40) is defined as values assumable by the one or more unknown variables. Values of the risk prediction function are computed over the at least one hyperplane using the obtained patient values. A visualization template is selected from a database of visualization templates (50) using template selection indices including the risk prediction function and the one or more unknown variables. Using the visualization template, a visualization (52) of the computed values of the risk prediction function over the at least one hyperplane is displayed.

Abstract: Methods and systems for selecting a treatment for a patient. The system extracts an incidental finding from a record associated with a patient and an associated follow-up recommendation. The system then determines whether any inconsistencies exist between the follow-up recommendation from the report and a follow-up recommendation prescribed by institutional or administrative guidelines. Any inconsistencies may then be resolved to guarantee an appropriate workflow for patient care.

Abstract: A system and method prioritizes and presents heterogenous medical data. The method includes retrieving medical data of a patient, the medical data including data from multiple data sources. The method includes phenotyping the medical data to generate a reasoning trail and reasoning outcome including one or more codes, the reasoning trail including a basis for which the reasoning outcome is determined. The method includes assigning a relevance score to each of the one or more codes. The method includes ranking the codes based on the relevance score of each of the one or more codes. The method includes displaying the codes in rank order.

Abstract: A computer-implemented method (40) reduces processing time of an application for visualizing image data, which application is one of a plurality of applications selectable by a user. Each of the plurality of applications includes a pre-processing algorithm for pre-processing the image data. The method predicts which one of the pre-processing algorithms is to be performed in response to a selection of an application by the user by: —extracting a feature vector from the image data, metadata, and/or additional data associated with the image data, —supplying the feature vector as input to a machine learned model, and —receiving an algorithm identifier as output from the machine learned model. The algorithm identifier identifies the pre-processing algorithm. Additionally, the algorithm identifier is used to select (42) the pre-processing algorithm. The image data is pre-processed (43) using the selected pre-processing algorithm.

Abstract: A patient monitor (8) includes a display (10). Patient values (38) are obtained for one or more known variables of a risk prediction function (30). One or more unknown variables of the risk prediction function are determined, and at least one hyperplane (40) is defined as values assumable by the one or more unknown variables. Values of the risk prediction function are computed over the at least one hyperplane using the obtained patient values. A visualization template is selected from a database of visualization templates (50) using template selection indices including the risk prediction function and the one or more unknown variables. Using the visualization template, a visualization (52) of the computed values of the risk prediction function over the at least one hyperplane is displayed.

Abstract: A computer-implemented method (40) of reducing processing time of an application for visualizing image data, the application being one of a plurality of applications selectable by a user and each of the plurality of applications comprising a pre-processing algorithm for pre-processing the image data.

Abstract: A computer-implemented method (40) of reducing processing time of an application for visualizing image data, the application being one of a plurality of applications selectable by a user and each of the plurality of applications comprising a pre-processing algorithm for pre-processing the image data.

Abstract: A system (100) for enabling study of image data, comprising: —a user interface subsystem (120) for i) receiving navigation commands (022) from a user, and ii) displaying different views (400) of the image data (042) in response to the navigation commands for enabling the user to navigate through the image data; —a function execution subsystem (160) for executing individual ones of a plurality of system functions (500) to support the user in the study of the image data; and—a pattern analysis subsystem (140) for: j) obtaining, from the user interface subsystem, data (022) indicative of a display sequence of the different views during the navigating through the image data, jj) analyzing the data to determine a navigation pattern (631) of the user, and jjj) based on the navigation pattern, selecting one of the plurality of system functions for execution by the function execution subsystem.

Abstract: A computer-implemented method (40) of reducing processing time of an application for visualizing image data, the application being one of a plurality of applications selectable by a user and each of the plurality of applications comprising a pre-processing algorithm for pre-processing the image data.

Abstract: A system and/or method that facilitates sharing image viewing context between vendor visualization applications without integration of different software application from different vendors packages is describe herein. In one instance, a visualization computing system (102) includes a processor (116) that executes computer readable instructions that capture a visual context of an imaging study displayed via a basic visualization application running on a vendor computing system, identify the study based on the captured visual context, load the study on the visualization computing system, and launch an advanced visualization application, which allows viewing and manipulation of the loaded study using advanced visualization tools unavailable by the basic visualization application.

Abstract: A system (100) for enabling study of image data, comprising:—a user interface subsystem (120) for i) receiving navigation commands (022) from a user, and ii) displaying different views (400) of the image data (042) in response to the navigation commands for enabling the user to navigate through the image data;—a function execution subsystem (160) for executing individual ones of a plurality of system functions (500) to support the user in the study of the image data; and—a pattern analysis subsystem (140) for: j) obtaining, from the user interface subsystem, data (022) indicative of a display sequence of the different views during the navigating through the image data, jj) analyzing the data to determine a navigation pattern (631) of the user, and jjj) based on the navigation pattern, selecting one of the plurality of system functions for execution by the function execution subsystem.