The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Nov. 28, 2023

Filed:

Dec. 31, 2022
Applicant:

Express Scripts Strategic Development, Inc., St. Louis, MO (US);

Inventors:

Amit K. Bothra, Wildwood, MO (US);

Pritesh J. Shah, Paramus, NJ (US);

Christopher G. Lehmuth, St. Louis, MO (US);

Bradley D. Flynn, St. Louis, MO (US);

Varun Tandra, McKinney, TX (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G16H 40/20 (2018.01); G06N 3/08 (2023.01); G06Q 50/00 (2012.01); G06Q 30/0201 (2023.01); G06Q 10/107 (2023.01); G16H 20/10 (2018.01); G16H 50/30 (2018.01); G16H 50/20 (2018.01); G16H 50/70 (2018.01); A61B 5/00 (2006.01); G16H 80/00 (2018.01); H04L 65/1066 (2022.01);
U.S. Cl.
CPC ...
G16H 40/20 (2018.01); A61B 5/4833 (2013.01); G06N 3/08 (2013.01); G06Q 10/107 (2013.01); G06Q 30/0201 (2013.01); G06Q 50/01 (2013.01); G16H 20/10 (2018.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01); G16H 50/70 (2018.01); G16H 80/00 (2018.01); H04L 65/1066 (2013.01);
Abstract

A method includes generating an intervention model by determining principal components for features of a training set, associating each feature of the training set with a principal component, selecting features of the training set most highly correlated with principal components, training a machine learning model with at least some of the selected features, and saving the verified trained machine learning model as the intervention model. The method includes determining multiple channel-specific intervention expectations. Each channel-specific intervention expectation indicates a likelihood that the user will take action in response to an intervention being executed using the engagement channel corresponding to the channel-specific intervention expectation. The method includes selecting an intervention and scheduling the selected intervention for execution.


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