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:
Jul. 16, 2024

Filed:

Jun. 08, 2020
Applicant:

Walgreen Co., Deerfield, IL (US);

Inventors:

Benjamin Weiss, Chicago, IL (US);

Ankur Jain, Chicago, IL (US);

Kate Louise Paduchowski, Hamtramck, MI (US);

Assignee:

WALGREEN CO., Deerfield, IL (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G16H 20/13 (2018.01); G06F 9/4401 (2018.01); G16H 10/00 (2018.01); G16H 10/60 (2018.01); G16H 20/10 (2018.01);
U.S. Cl.
CPC ...
G16H 20/13 (2018.01); G06F 9/4418 (2013.01); G16H 10/60 (2018.01); G16H 20/10 (2018.01); G16H 10/00 (2018.01);
Abstract

A computing system for adaptive prescription reminders includes a processor and a memory storing instructions that, when executed by the processor, cause the system to receive a fill event, generate an initial schedule, receive an medication consumption indication, generate an updated schedule using a trained machine learning model, cause the updated schedule to be displayed, and receive a patient confirmation. A computer-implemented method includes receiving a fill event, generating an initial schedule, receiving an medication consumption indication, generating an updated schedule using a trained machine learning model, causing the updated schedule to be displayed, and receiving a patient confirmation. A non-transitory computer readable medium includes program instructions that when executed, cause a computer to: receive a fill event, generate an initial schedule, receive an medication consumption indication, generate an updated schedule using a trained machine learning model, cause the updated schedule to be displayed, and receive a patient confirmation.


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