Abstract: Techniques and system configurations to enable the automated collection and evaluation of clinical data within an automated insights information system are disclosed herein. In an example, the information system is adapted to continuously monitor clinical systems for new patient data, process patient data into a standardized and structured format, selectively run algorithms to classify and characterize data, and stores the results of algorithms (such as findings, predictions, and recommendations) that can be used as input to other algorithms, or sent to clinical systems and presented to end users. In a specific example, a method performed in a computing system may include: requesting and obtaining a first and second set of clinical data, analyzing the first and second set of clinical data with respective algorithms, identifying a clinical finding, and generating output from the computing system based on the identified clinical finding.

Abstract: Techniques for training a deep neural network from user interaction workflow activities occurring among distributed computing devices are disclosed herein. In an example, processing of input data (such as input medical imaging data) is performed at a client computing device with the execution of an algorithm of a deep neural network. A set of updated training parameters are generated to update the algorithm of the deep neural network, based on user interaction activities (such as user acceptance and user modification in a graphical user interface) that occur with the results of the executed algorithm. The generation and collection of the updated training parameters at a server, received from a plurality of distributed client sites, can be used to refine, improve, and train the algorithm of the deep neural network for subsequent processing and execution.

Abstract: This document discusses, among other things, a computerized system comprising a perfusion analyzer circuit and a memory circuit to store a time sequence of volumetric image data. The image data is obtained in a time relation to arrival of a contrast agent at an anatomical region associated with the image. The perfusion analyzer circuit is configured to access the stored image data and receive a representation of an artery and a representation of tissue near the artery, shift the representation of the artery in time such that a time of arrival of the contrast at the artery precedes arrival of the contrast at the representation of tissue, automatically compute a perfusion parameter using the shifted representation of the artery, and provide the perfusion parameter as an output to a user or to an automated process.

Abstract: Apparatus and methods for monitoring activity use video information to track activity of a target at a given location. In an embodiment, the target is segmented into portions and a value of a biometric attribute is associated with the target and compared against values of a biometric attributes of corresponding portions of other images to identify the target and determine a length of time that the target is at the given location.