Accenture Global Solutions Limited

Christopher Donnelly

Andrew John Truscott

Ethan Bischoff

Jean M Becker

Shinichiro Shuda

Todd Bremer

Praveen Kishorepuria

Vivek Nadiminti

Barton FitzGerald Keery

Kanwar Inder Singh

Aaron L Shifrin

Harshavardhan Basantkumar Kar

A device obtains prescription information relating to a medication in a container. The device causes a camera device of the device to obtain image data relating to the medication and a weighing device of the device to obtain weight data relating the medication. The device sends the prescription information, the image data, and the weight data to a different device to cause the different device to verify the medication using a machine learning model. The device receives information concerning the medication and automatically generates, based on the information concerning the medication, a message concerning the medication, wherein the message includes instructions on how much of the medication a user of the device is to take. The device causes the device or an additional device to present the message.

Identification and verification of medication

A self-learning system for analytical attribute and clustering segmentation may be provided. A text classifier may identify a log description of a log entry in response to text of the log description being associated with indicators of a word model. A datafield classifier may generate a datafield metrics including an accuracy value of the attribute identifiers representing the datafield. A metafield classifier may generate a context metrics for the context of the log entry, the context metrics including an accuracy value of the attribute identifiers representing the metafields. A combination classifier may form a weighted classification set and select an attribute identifier as being representative of the datafield based on the weighted classification set. The combination classifier may further evaluate an attribute importance value of each attribute identifier, and select an attribute identifier having a top attribute importance value.

Self-learning analytical attribute and clustering segmentation system

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Winnetka, IL, United States of America

Christopher Donnelly