Abstract: An example computer-implemented method includes receiving, via a processor, a dataset of objects to be tested for positivity violations. The method includes generating, via the processor, a feature matrix based on features extracted from the objects. The method also includes generating, via the processor, decision trees to group the objects into homogenous groups based on entropy and generate a random forest to compute consistency of violations. The method further includes detecting, via the processor, a positivity violation based on an entropy threshold, a consistency threshold, and a statistical significance threshold being exceeded. The method further includes generating, via the processor, an interactive representation to display the positivity violation.

Abstract: An example system includes a processor to receive a number of videos. The processor is to generate a number of image clouds based on the videos. The processor is to present an interactive image cloud representation including the image clouds. Each image cloud includes a representative image and a number of associated images.

Abstract: A system for managing medical events, includes: at least one medical sensor, configured to output a plurality of sensor measurements; at least one display; at least one hardware processor connected to the medical sensor and the display, and adapted to: receive a plurality of events, each having a time of occurrence, including the plurality of measurements and a plurality of external events; identify a target sequence of events in the plurality of events; identify in the plurality of events a plurality of matching sequences, each including a sequence of events matching the target sequence; augment each of the matching sequences with some temporally related events according to a predefined time test; cluster the plurality of augmented sequences in a plurality of clusters according to a temporal distribution of events; and display on the display a visual representation of the plurality of clusters according to a predefined set of similarity criteria.

Abstract: A computer-implemented method, computerized apparatus and computer program product for hierarchical objects linkage data visualization. A visualization of linkage data comprising a plurality of connections between a set of source objects and a set of target objects is obtained with respect to a predetermined level of hierarchy defined over attributes of at least one of the sets, wherein attributes of the objects and connections therebetween are represented in the visualization as nodes and links of a bipartite graph respectively. A spatial layout of links of a node is modified based on a relative position of each neighbor node thereof in an adjacent level, wherein neighboring nodes represent attributes of one or more objects which share in common an attribute represented by the node, wherein the relative position is determined based on a visualization restricted to the neighboring nodes so as to obtain a position preserving layout.

Abstract: An example system includes a processor to receive a number of videos. The processor is to generate a number of image clouds based on the videos. The processor is to present an interactive image cloud representation including the image clouds. Each image cloud includes a representative image and a number of associated images.

Abstract: An example computer-implemented method includes receiving, via a processor, a dataset of objects to be tested for positivity violations. The method includes generating, via the processor, a feature matrix based on features extracted from the objects. The method also includes generating, via the processor, decision trees to group the objects into homogenous groups based on entropy and generate a random forest to compute consistency of violations. The method further includes detecting, via the processor, a positivity violation based on an entropy threshold, a consistency threshold, and a statistical significance threshold being exceeded. The method further includes generating, via the processor, an interactive representation to display the positivity violation.

Abstract: An example system includes a processor to receive temperature data from a plurality of sensors disposed at locations more sensitive to temperature change in a plurality of server racks. The processor is to also generate a statistical model comprising a continuous spatial statistical distribution of temperature values based on the temperature data. The processor is to further generate a pseudo heat map based on the statistical model.

Abstract: A pathway for each entity in a cohort may be extracted from raw data comprising a plurality of events. A common graph structure may be created based the extracted pathways. For each cohort, a relative signature trait may be computed for each edge based on a number of appearances of the edge in the extracted pathways that are associated with the cohort. A relationship expression may be obtained. The relationship expression may be with respect to at least two cohorts for which relative signature traits were computed. The common graph structure may be processed based on the relationship expression to determine an output label for each edge. A visualization of the common graph structure may be displayed.

Abstract: A computer-implemented method, computerized apparatus and computer program product for efficient solution of nearest object problems. A set of objects having non-point shapes representable by one or more geometric elements are obtained. For each object in the set the one or more geometric elements are sampled to obtain a set of points representing the set of objects. A Voronoi diagram is constructed for the set of points, whereby a subdivision of a space accommodating the set of objects into a plurality of cells, each cell containing a single point of the set of points and defining a region of closest neighbors of the point, is obtained. Cells containing points representing the same object are aggregated into a unified cell defining an estimated region of closest neighbors of the object.

Abstract: There is provided a method of creating a cohort clinical pathway graph based on knowledge-driven manual user input and automated data-driven mining comprising: receiving via a graphical user interface (GUI), manual selections including: knowledge-driven variable(s) denoting clinically significant values representing elements of a clinical decision making process, and an anchoring location of each knowledge-driven node denoting a respective knowledge-drive variable within a directed acyclic graph (DAG), computing individual clinical pathways for each of the sampled population of patients by automatically computing data-driven nodes denoting the data-driven discovery of event types relative to the manual selections, and aggregating the individual clinical pathways to compute a cohort clinical pathway DAG, wherein the cohort clinical pathway DAG includes nodes comprising the knowledge-driven nodes, the data-driven nodes, and links connecting the nodes, each link denoting an automatically discovered sequence betw

Abstract: A pathway for each entity in a cohort may be extracted from raw data comprising a plurality of events. A common graph structure may be created based the extracted pathways. For each cohort, a relative signature trait may be computed for each edge based on a number of appearances of the edge in the extracted pathways that are associated with the cohort. A relationship expression may be obtained. The relationship expression may be with respect to at least two cohorts for which relative signature traits were computed. The common graph structure may be processed based on the relationship expression to determine an output label for each edge. A visualization of the common graph structure may be displayed.

Abstract: A computer-implemented method, computerized apparatus and computer program product for hierarchical objects linkage data visualization. A visualization of linkage data comprising a plurality of connections between a set of source objects and a set of target objects is obtained with respect to a predetermined level of hierarchy defined over attributes of at least one of the sets, wherein attributes of the objects and connections therebetween are represented in the visualization as nodes and links of a bipartite graph respectively. A spatial layout of links of a node is modified based on a relative position of each neighbor node thereof in an adjacent level, wherein neighboring nodes represent attributes of one or more objects which share in common an attribute represented by the node, wherein the relative position is determined based on a visualization restricted to the neighboring nodes so as to obtain a position preserving layout.

Abstract: There is provided a method of creating a cohort clinical pathway graph based on knowledge-driven manual user input and automated data-driven mining comprising: receiving via a graphical user interface (GUI), manual selections including: knowledge-driven variable(s) denoting clinically significant values representing elements of a clinical decision making process, and an anchoring location of each knowledge-driven node denoting a respective knowledge-drive variable within a directed acyclic graph (DAG), computing individual clinical pathways for each of the sampled population of patients by automatically computing data-driven nodes denoting the data-driven discovery of event types relative to the manual selections, and aggregating the individual clinical pathways to compute a cohort clinical pathway DAG, wherein the cohort clinical pathway DAG includes nodes comprising the knowledge-driven nodes, the data-driven nodes, and links connecting the nodes, each link denoting an automatically discovered sequence betw

Abstract: Visualizations of a serial process are provided. A process model of a serial process is constructed using an underlying statististical model. The process model represents each instance of the serial process as a series of interconnected nodes, wherein (i) the serial process includes a plurality of events; (ii) each node is associated with an event and a time at which the associated event occurred in an instance of the serial process; and (iii) connectors link nodes together to form the series of interconnected nodes, the connectors representing stages of serial process. The stages are scored and categorized into various categories based, at least in part, on the process model. One or more of the categories is associated with outlier stages. A visualization of the process model is presented such that the visualization associates the stages of the instances of serial process with respective categories.

Abstract: A system for managing medical events, includes: at least one medical sensor, configured to output a plurality of sensor measurements; at least one display; at least one hardware processor connected to the medical sensor and the display, and adapted to: receive a plurality of events, each having a time of occurrence, including the plurality of measurements and a plurality of external events; identify a target sequence of events in the plurality of events; identify in the plurality of events a plurality of matching sequences, each including a sequence of events matching the target sequence; augment each of the matching sequences with some temporally related events according to a predefined time test; cluster the plurality of augmented sequences in a plurality of clusters according to a temporal distribution of events; and display on the display a visual representation of the plurality of clusters according to a predefined set of similarity criteria.

Abstract: A computer-implemented method, computerized apparatus and computer program product for efficient solution of nearest object problems. A set of objects having non-point shapes representable by one or more geometric elements are obtained. For each object in the set the one or more geometric elements are sampled to obtain a set of points representing the set of objects. A Voronoi diagram is constructed for the set of points, whereby a subdivision of a space accommodating the set of objects into a plurality of cells, each cell containing a single point of the set of points and defining a region of closest neighbors of the point, is obtained. Cells containing points representing the same object are aggregated into a unified cell defining an estimated region of closest neighbors of the object.

Abstract: A computer-implemented method, computerized apparatus and computer program product for efficient solution of nearest object problems. A set of objects having non-point shapes representable by one or more geometric elements are obtained. For each object in the set the one or more geometric elements are sampled to obtain a set of points representing the set of objects. A Voronoi diagram is constructed for the set of points, whereby a subdivision of a space accommodating the set of objects into a plurality of cells, each cell containing a single point of the set of points and defining a region of closest neighbors of the point, is obtained. Cells containing points representing the same object are aggregated into a unified cell defining an estimated region of closest neighbors of the object.

Abstract: A method, apparatus and computer program product for Functional Space-Time Trajectory Clustering. The method comprises receiving collections of data structures comprising location and time descriptors. The method further comprises estimating functional curves from the collections of data structures. The method further comprises reducing dimensions of the functional curves; and clustering the functional curves into clusters.

Abstract: According to some embodiments of the present invention there is provided a computerized method for visually modifying a rule. The method may comprise receiving a rule and two or more data records, the rule comprising two or more computation instructions and each one of the data records comprising one or more physical location value. The method may comprise displaying a simulation comprising visual objects, each of the visual objects showing a result of applying the rule to one of the data records, and displayed on a computerized display at a position corresponding to the physical location value of the data records. The method may comprise receiving a marking from a user of one or more of the visual objects on the computerized display. The method may comprise modifying the computation instructions to produce a modified rule, based on the markings, and sending the modified rule.

Abstract: A capability to visualize temporal aspects of serial processes is provided. A process model of a serial process that includes a plurality of events and a plurality of stages is generated. The process model represents each of one or more instances of the serial process as a series of nodes. Each node represents an event and a time at which the event occurred in an instance of the serial process. For each stage of the serial process, a time-coordinate of a first node and a time-coordinate of a second node are altered while maintaining a difference in time between the first and second nodes. A common point lies between the first and second nodes as a result of altering the time-coordinates. A visualization of the process models is presented such that, for each stage of the serial process, a plurality of line segments intersect at the common point.