C/hca, Inc.

Hca Holdings, Inc.

Janet McCallister

Vincent Doyle, Iii

David Charles Sanderson

Lisa Ann Pitts

Marne Lynn Owens

Sarah Dhane

Dan Nguyen

James E Hicks

George Tucker

Christopher Anthony

Heather Fuller

Chigger Bynum

Sameer Sunilkumar David

Thomas Neal Payne

Erica Williams

Robert Barnett Rhodes

Scott Murray

Tara Haines

Randy Scott Fagin

Gina Marie Ragans

Edmund Stephen Jackson

Megan McGee

Brooke Hamilton

Hannah Marshall

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.

Utilizing predictive modeling to identify anomaly events

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.

Customizable real-time electronic whiteboard system

In some examples, there may be provided systems, devices, and methods for using data from disparate sources to determine whether diversion events have occurred. A diversion event may be when a monitored unit intended for a target user is diverted away from the target user.

Aggregating data to identify diversion events

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Tallahassee, FL, United States of America

Janet McCallister