Abstract: In some examples, there may be provided systems, devices, and methods for using data from disparate databases to determine characteristics of a set of users within an organizational unit and generate customized user interface elements for display within a user interface.

Abstract: Approaches are provided for a prediction model determining a prediction indicative of the authorized user being associated with at least one anomaly event. In one example, a computer system may receive data from different sources. For example, the system may receive data associated with use of one or more monitored units of an automated storage and retrieval location. The system may also receive request data associated with a request for execution of the monitored controlled unit by an authorized user to a target user. The prediction model of the system may utilize the received data to determine the prediction that the authorized user is associated with at least one anomaly event associated with a diversion of a monitored unit away from the target user. The system may then provide the prediction for presentation.

Abstract: A method and system for initiating message listening and routing message content to authorized user devices is disclosed. For a second user device to receive notifications regarding records of a first user, the second user device provides information identifying the first user to a notification service. The notification service verifies the identifying information. The notification service initiates one or more listeners to listen for messages flowing over a messaging bus that are relating to the first user. Once a message is identified, at least a portion of the message is used to generate a notification that may be sent to the second user device.

Abstract: Electronic communications received via a network from a plurality of electronic devices may include signals of device interactions or data changes that correspond to process performances by process-performing resources, signals of conditions of loads, or signals of processes associated with the process-performing resources and the loads. Data composites may be formed from the electronic communications, with data portions collected and mapped to resource profile records and load profile records that may be updated with the collected data portions. For each load, at least one of the one or more resource profile records and/or the one or more load profile records may be used to map the process-performing resources to the load. Content nodes may be linked in a network of content nodes, including respective linked content, resource specifications or load specifications. Access to the network of content nodes may be allowed via a control interface.

Abstract: Systems, methods, and machine-readable storage media for processing data streams in accordance with protocols to selectively transmit content to endpoint devices to facilitate conferencing are disclosed. Electronic communications may be received, via one or more networks, from endpoint devices, segregated, and routed to facilitate conferencing environments. Listening for data changes in data streams may be performed, each data stream corresponding to a particular source. Data changes that are generated based on events may be detected and mapped to a particular load identifier and a particular conferencing environment. A conferencing protocol may be identified and mapped to the particular conferencing environment. Consequent to determining that the data changes correspond to the one or more, the particular conferencing environment may be updated.

Abstract: Electronic communications received via a network from a plurality of electronic devices may include signals of device interactions or data changes that correspond to process performances by process-performing resources, signals of conditions of loads, or signals of processes associated with the process-performing resources and the loads. Data composites may be formed from the electronic communications, with data portions collected and mapped to resource profile records and load profile records that may be updated with the collected data portions. For each load, at least one of the one or more resource profile records and/or the one or more load profile records may be used to map the process-performing resources to the load. Content nodes may be linked in a network of content nodes, including respective linked content, resource specifications or load specifications. Access to the network of content nodes may be allowed via a control interface.

Abstract: In some examples, systems, methods, and devices are described that generate contextual suggestions for patients. Generation of the contextual suggestions is triggered by certain events performed by a medical professional with respect to a patient (e.g., updating a patient record). The contextual suggestions are related to addressing health conditions of the patient and represent tasks or considerations which the medical professional should be made aware. The contextual suggestions are generated in a way that is considerate of patient context, medical professional context, and contexts of similar patients. The contextual suggestions can be presented to the medical professional for selection and execution.

Abstract: Approaches are provided for a prediction model determining a prediction indicative of the authorized user being associated with at least one anomaly event. In one example, a computer system may receive data from different sources. For example, the system may receive data associated with use of one or more monitored units of an automated storage and retrieval location. The system may also receive request data associated with a request for execution of the monitored controlled unit by an authorized user to a target user. The prediction model of the system may utilize the received data to determine the prediction that the authorized user is associated with at least one anomaly event associated with a diversion of a monitored unit away from the target user. The system may then provide the prediction for presentation.

Abstract: In some examples, a prediction is generated by a prediction system. A machine learning model of the prediction system receives as input one or more data elements of a user service record, and outputs a prediction, the prediction corresponding to one or more probability scores. The one or more probability scores correspond to a prediction that a user will exhibit a certain behavioral pattern (e.g., probability of readmission to a service unit within a predefined post-release time period) and/or be classified into a certain service category (e.g. probability of association with a particular service group, the service group being included within a set of qualifying service groups). The prediction system may then provide the prediction to a user device of a user coordinator for subsequent presentation on the user device to assist the user coordinator in coordinating user service.

Abstract: In some examples, unstructured data is evaluated using a natural language processing model to output a set of subjective indicators. These subjective indicators are scored using a predictive model to determine whether a dependent user has or is likely to develop a particular condition such as a cellular abnormality.

Abstract: The techniques may include receiving patient data of patients of a service facility, each patient assigned to a service unit. In addition, the techniques may include inputting patient data into a classification model trained to output classifications. The techniques may include determining a classification for each patient. Moreover, the techniques may include assigning each patient to a patient group based at least in part on a classification common with members of the patient group. The techniques may include determining a recommendation associated with at least one of: (1) servicing a first service resource associated with a third service unit, or (2) procuring a second service resource associated with a fourth service unit. This recommendation can be based at least in part on the classifications. Further, the techniques may include presenting on a user device of a patient care provider for coordinating patient care among service units of the service facility.

Abstract: Techniques are disclosed for providing a data feed, associated with a servicing of a particular user, to a device assigned to a particular location within a service facility for presentation of the data feed to a display at the particular location. In one example, the techniques include a system receiving a request from the device for the data feed, the request being independent of the particular user being serviced at the particular location. The system may determine that the particular user is being serviced at the particular location, and then retrieve first data and second data associated with the user, respectively from a first and second data source of a plurality of data sources. The system may then generate the data feed including at least the first data and the second data, and provide the data feed to the device for presentation at the display at the particular location.

Abstract: Approaches are provided for a prediction model determining a prediction indicative of the authorized user being associated with at least one anomaly event. In one example, a computer system may receive data from different sources. For example, the system may receive data associated with use of one or more monitored units of an automated storage and retrieval location. The system may also receive request data associated with a request for execution of the monitored controlled unit by an authorized user to a target user. The prediction model of the system may utilize the received data to determine the prediction that the authorized user is associated with at least one anomaly event associated with a diversion of a monitored unit away from the target user. The system may then provide the prediction for presentation.

Abstract: In some examples, there may be provided systems, devices, and methods for using data from disparate databases to determine characteristics of a set of users within an organizational unit and generate customized user interface elements for display within a user interface.

Abstract: In some examples, systems, methods, and devices are described that generate contextual suggestions for patients. Generation of the contextual suggestions is triggered by certain events performed by a medical professional with respect to a patient (e.g., updating a patient record). The contextual suggestions are related to addressing health conditions of the patient and represent tasks or considerations which the medical professional should be made aware. The contextual suggestions are generated in a way that is considerate of patient context, medical professional context, and contexts of similar patients. The contextual suggestions can be presented to the medical professional for selection and execution.

Abstract: Techniques are disclosed for assigning a user to a particular user navigation program among a plurality of user navigation programs. The techniques include receiving user data associated with a user record of a user. The techniques further include inputting the user data into a segmentation model of a user navigation system to classify a user within a segment, whereby the segmentation model outputs a score that is determined to be in accordance with a classification threshold. The user navigation system further detects an occurrence of a trigger based in part on the user classification within the segment, and then prioritizes the user among other users based on the detected occurrence of the trigger. The user navigation system then assigns the user to a particular user navigation program based at least in part on the determined priority of the user.

Abstract: Described herein is a system in which multiple display devices may be located remotely throughout a facility. The system receives location information for a number of users within the facility. The system is able to identify a set of users collocated with a particular display device and generate a set of configuration settings specific to that set of users. Information provided by the system, either in response to an information request or automatically, may be formatted and/or filtered according to the generated set of configuration settings. In some embodiments, the set of configuration settings may be compiled from each of the users in the set of users based on priority.

Abstract: Electronic communications received via a network from a plurality of electronic devices may include signals of device interactions or data changes that correspond to process performances by process-performing resources, signals of conditions of loads, or signals of processes associated with the process-performing resources and the loads. Data composites may be formed from the electronic communications, with data portions collected and mapped to resource profile records and load profile records that may be updated with the collected data portions. For each load, at least one of the one or more resource profile records and/or the one or more load profile records may be used to map the process-performing resources to the load. Content nodes may be linked in a network of content nodes, including respective linked content, resource specifications or load specifications. Access to the network of content nodes may be allowed via a control interface.

Abstract: In some examples, a data stream processing system is provided for processing data streams so as to extract and transmit pertinent information from the data streams to devices or systems. More specifically, the data stream processing system can facilitate a selective, reliable and efficient processing of data elements within the data streams.

Abstract: Techniques are disclosed for coordinating service for a user assigned to a service unit of a service facility. The techniques include receiving user data associated with the user, or resource status data associated with a status of a resource. The techniques further include determining a classification of the user based on the user data, the classification corresponding to a condition or service status of the user. The user may then be assigned to a user group based on the classification of the user. The user group may be associated with a recommendation for treating the user. The resource may also be assigned to a resource group based on the resource status data. The techniques further include generating a visual representation of at least a portion of the service unit based on the assigned user group or assigned resource group, and providing the visual representation to a user device for presentation.