Microsoft Technology Licensing, LLC

Physio-control, Inc.

Alexander Esibov

Vitaly Khait

Robert G Walker

Mitchell Allen Smith

Guy Lewin

Tyson G Taylor

Ami Luttwak

Fred William Chapman

Isabelle L Banville

Randy L Merry

Itamar Azulay

Yossi Haber

Robert P Marx

A file is enabled to be downloaded from a web server on behalf of a client browser, via an isolated browser of an RBI server. An isolated browser engine detects the file download and notifies an isolated browser controller. The isolated browser controller determines whether the file download is permitted. Responsive to determining that the file download is not permitted, the file is deleted at the RBI server and a policy event is transmitted to the client browser. Responsive to determining that the file download is permitted, the file is transmitted to the client browser. The file may be streamed to the client browser, or it may be published via an independent web server and a notification is transmitted to the client browser. The client browser is controlled to issue a request to the independent web server to download the file to the client browser.

Inline file download controls in remote browser isolation system

A prehospital telemedicine system comprises a physiologic monitor; an electronic patient care reporting system (ePCR) system; and a point-of-care blood analyzer communicatively coupled to the physiologic monitor and the ePCR system. The point-of-care blood analyzer is configured to perform an analysis of a blood sample based on an indication of a need for a specific blood analysis provided by one of the physiologic monitor and the ePCR system, and to automatically transmit a result of the analysis to a remote data receiving system. The indication of a need for a specific blood analysis may be based upon any one of the following: vital signs data obtained for a patient by the physiologic monitor; and/or current documentation or past medical history captured on or available through the ePCR system.

Integration of a point-of-care blood analyzer into a prehospital telemedicine system

Systems and methods are provided for managing dynamic controls over access to computer resources and, even more particularly, for evaluating and re-evaluating dynamic conditions and changes associated with user sessions. The systems and methods are configured to automatically make a determination as to whether new or additional authentication credentials are required for a user that is already authorized for accessing resources in a user session, in response to triggering events such as the identification of a new or changed condition associated with the user session.

Enforce changes in session behavior based on updated machine learning model with detected risk behavior during session

Providing fluid external access to a resource that is internal to a network from external to that network. From within the network, the internal user simply provides an internal identifier, and the external user accesses not the internal identifier, but an external uniform resource identifier (URL) that the external user can simply select to obtain access to the internal resource of the network. This is accomplished by translating the internal identifier to an external URL having a proxy server as its domain name. When the external URL selects the URL, a request with that external URL is made to the proxy server, which translates the external URL back to the internal identifier, and coordinates with the network to obtain the resource for the external user.

External access to internal network resource

Embodiments operate in contexts where field data have been generated from a field event, and annotations have been generated from the field data, which purport to identify events within the field data, such as CPR compressions and ventilations. Metrics are generated from the annotations, which are used in training. In such contexts, a grade may be assigned that reflects how well the annotations meet one or more accuracy criteria. The grade may be used in a number of ways. Reviewers may opt to disregard field data and metrics that have a low grade. Expert annotators may be guided as to precisely which annotations to revise, saving time. A low grade may decide that the results are not emailed to reviewers, but to annotators. A learning medical device can use the grade internally to adjust its own internal parameters so as to improve its annotating algorithms.

Automatically evaluating likely accuracy of event annotations in field data

Growing community of inventors

Seattle, WA, United States of America

Alexander Esibov