Hewlett-packard Development Company, L.p.

Hewlett Packard Enterprise Development LP

General Electric Company

Ge Precision Healthcare LLC

Entit Software LLC

Hewlett-packard Indigo B.v.

Staelin, Carl

Kisilev, Pavel

Schein, Sagi

Banner, Ron

Sagi Schein

Ruth Bergman

Omer Barkol

David Lehavi

Ayelet Pnueli

Michael Pogrebisky

Doron Shaked

Carl Staelin

Pavel Kisilev

Renato Keshet

Ron Maurer

Mani Fischer

Hila Nachlieli

Marie Vans

Ludovic Avot

Daniel Freedman

Anastasia Dubrovina

Jeffrey Hersh

Steven J Simske

Menachem Halmann

Ilan Shufer

Naomi Sato

Paul Lawrence Mullen

Ram Dagan

Ron Banner

Rodolfo Jodra

Alexei Ledenev

Igor Nor

Gidi Amir

Marianne Hickey

Nitsan Amichai

Yonathan Livny

Eyal Hayun

Paul Mullen

Inbal Tadeski

Vitali Greenberg

Edwar Bkheet

Avi Malki

Vitaly Burshtein

Antonio Zaitoun

Ole Jakob Utkilen

Alexei Lenedev

Ayelel Pnueli

Various systems and devices are provided for facilitating communication in a healthcare setting. In one example, a system for providing medical information can include a processor that, in response to executing machine-readable instructions, can generate a patient dashboard comprising the medical information for a patient and a patient communication thread. The processor can also output the patient dashboard to a display, wherein the patient dashboard further comprises a first link proximate to a displayed parameter from the medical information and the processor can obtain communication among care providers monitoring the patient and virtual healthcare assistants configured to communicate on the communication thread. The processor can also output the communication from the care providers, the virtual healthcare assistances, or any combination thereof, in the patient communication thread of the patient dashboard provided by the display.

Devices and method for a healthcare collaboration space

Techniques are described that facilitate online monitoring of clinical data streams in association with detecting missing data and other suspicious data deviations. According to an embodiment, a computer implemented comprises receiving, by a system comprising a processor, a data stream from a plurality of different clinical data information systems configured to report defined clinical events within the data stream and recording arrival times of received events of the defined clinical events. The method further comprises detecting, by the system, data failure events associated with the data stream based on time differences between the arrival times for defined clinical events of the same type and estimated probabilities that the time differences are expected, wherein the detecting comprises estimating the probabilities that the time differences are expected using time-to-event models developed for each of the defined clinical events of the same type.

Online monitoring of clinical data drifts

Real-time alerts and transmission of selected signal samples is disclosed. One example is a system including a base facility linked to a production station with an alerting system to perform anomaly analysis utilizing an anomaly model. A receiver at the base facility receives, from the production station, a selection of signal samples based on the anomaly analysis, where the received selection is optimized at the production station to be substantially relevant to an update of a statistical model while adhering to a dynamic capacity limitation of the production station. The statistical model is maintained at the base facility and incorporates features related to the production station. A management system at the base facility updates the statistical model based on the received selection, optionally derives an updated anomaly model based on the statistical model, and optionally transmits the updated anomaly model to the production station.

Real-time alerts and transmission of selected signal samples under a dynamic capacity limitation

Methods and systems are provided for tracking anatomical features across multiple images. One example method includes outputting, for display on a display device, an annotation indicative of a first location of an identified anatomical feature of a first ultrasound image, the annotation generated based on a first output of a model and outputting, for display on the display device, an adjusted annotation based on a second output of the model, the second output of the model generated based on a second ultrasound image and further based on the first output of the model, the adjusted annotation indicative of a second location of the identified anatomical feature in the second ultrasound image.

System and methods for tracking anatomical features in ultrasound images

Various systems and devices are provided for facilitating communication in a healthcare setting. In one example, a system includes a display and a computing device operably coupled to the display. The computing device stores instructions executable to output, to the display, a patient-specific dashboard including medical information specific to the patient, the dashboard further including a displayed link to a patient-specific communication thread; and responsive to a user selecting the link, output to the display a portion of the communication thread, where the communication thread includes communication among one or more care providers monitoring the patient and one or more virtual healthcare assistants.

A method, a computing system, and a non-transitory machine readable storage medium containing instructions for identifying relationships between entities are provided. In an example, the method includes receiving a query. The query specifies a first computing entity, a second computing entity, and a window of time. A data structure is queried based on the query to identify a set of relationship instances each corresponding to a relationship between the first computing entity and the second computing entity during the window of time. A representation of the first computing entity, the second computing entity, and the set of relationship instances is provided at a user interface.

Identifying relationship instances between entities

In one implementation, a plurality of signature vectors from a multi-dimensional representation of a graphical object is generated. Each of the signature vectors comprises attributes that vary little in response to changes in shape, size, orientation, and visual layer appearance of the graphical object, and each of the signature vectors includes attributes based on operations of integration, differentiation, and transforms on the multi-dimensional representation of the graphical object. Each signature vector is composited into multiple portions from the plurality of signature vectors to define an appearance-invariant signature of the graphical object.

Graphical object appearance-invariant signature

In one implementation, an image-based automation process includes identifying a graphical object of a graphical user interface and performing an action relative to the graphical object at the graphical user interface. The identifying is based on an image including the graphical object.

Image-based automation systems and methods

A non-transitory storage device containing software than, when executed by a processor, causes the processor to generate a projection set of polynomials based on a projection of a space linear combination of candidate polynomials of degree d on polynomials of degree less than d that do not evaluate to less than a threshold on a set of points. The software also causes the processor to compute the singular value decomposition of a matrix containing the difference between candidate polynomials evaluated on the points and the projection set of polynomials evaluated on the points, and to partition the polynomials resulting from the singular value decomposition based on a threshold.

Generating and partitioning polynomials

In one implementation, a graphical object classification system includes an acquisition module, a signature generation module, and a classification module. The acquisition module accesses a representation of a graphical object. The signature generation module generates an appearance-invariant signature of the graphical object based on the representation. The classification module classifies the graphical object based on the appearance-invariant signature.

Graphical object classification

Systems, methods, and other embodiments associated with graphical user interface (GUI) component classification are described. One example method includes generating a first vector. The first vector may be generated based on image data describing a GUI component. The example method may also include assigning a GUI component classifier to the GUI component. Assigning the GUI component classifier may comprise comparing the first vector to members of a vector set. Members of the vector set may describe GUI elements. The example method may also include providing the GUI component classifier.

Graphical user interface component classification

A method includes obtaining, by executing a module stored on a non-transitory computer-readable storage device, approximately-zero polynomials for each of multiple classes. The method further includes evaluating the approximately-zero polynomials for each class on a plurality of points to compute distances from each point to each of the classes. The method also includes scaling the approximately-zero polynomials based on the distances and classifying the points based on the scaled approximately-zero polynomials.

Multiclass classification of points

Tasks are mapped to execution threads of a parallel processing device. Tasks are mapped from the list of tasks to execution threads of the parallel processing device that are free. The parallel processing device is allowed to perform the tasks mapped to the execution threads of the parallel processing device for a predetermined number of execution cycles. When the parallel processing device has performed the tasks mapped to the execution threads of the parallel processing device for the predetermined number of execution cycles, the parallel processing device is suspended from further performing the tasks to allow the parallel processing device to determine which execution threads have completed performance of mapped tasks and are therefore free.

Mapping tasks to execution threads

Automated inspection method for detecting a defect in a printed image, comprising processing a raster image, sending the raster image to a print process, printing a printed image corresponding to the raster image onto a medium, capturing a target image from at least a part of the printed image at a lower resolution than the printed image, at least in a medium moving direction, converting at least a part of the raster image to a reference image, and comparing the reference image to the target image.

Automated inspection of a printed image

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Haifa, Israel

Sagi Schein