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:
Aug. 08, 2023

Filed:

Oct. 16, 2020
Applicant:

Duke University, Durham, NC (US);

Inventors:

Rebecca Ann Schroeder, Durham, NC (US);

Nigel Benjamin Neely, Durham, NC (US);

Timothy William Dunn, Durham, NC (US);

Evan S. Frasure, III, Cary, NC (US);

Erich Senin Huang, Durham, NC (US);

Joseph Puthenveetil Mathew, Durham, NC (US);

Assignee:

Duke University, Durham, NC (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G16H 40/20 (2018.01); G16H 20/13 (2018.01); G16H 50/20 (2018.01); G16H 70/20 (2018.01); G16H 10/60 (2018.01); G16H 50/70 (2018.01); G06Q 10/105 (2023.01); G06Q 10/0639 (2023.01); G06N 20/20 (2019.01); G16H 70/40 (2018.01); A61J 7/00 (2006.01);
U.S. Cl.
CPC ...
G16H 40/20 (2018.01); G06N 20/20 (2019.01); G06Q 10/06398 (2013.01); G06Q 10/105 (2013.01); G16H 10/60 (2018.01); G16H 20/13 (2018.01); G16H 50/20 (2018.01); G16H 50/70 (2018.01); G16H 70/20 (2018.01); G16H 70/40 (2018.01); A61J 7/0076 (2013.01);
Abstract

According to one method for using machine learning in detecting drug diversion, the method comprises receiving, as input, an observed drug dispensation amount associated with a drug dispensation event related to a drug provider along with other drug dispensation event data, wherein the drug dispensation event data comprises drug provider information, procedure information, and patient information; generating, using a trained drug diversion detection algorithm and the drug dispensation event data, an expected drug dispensation amount associated with the drug dispensation event and determining, using the observed drug dispensation amount and the expected drug dispensation amount, whether the observed drug dispensation amount is aberrant, wherein the drug diversion detection algorithm includes at least one machine learning algorithm and is trained using one or more data sets associated with related drug dispensation events; and outputting, by the drug diversion detection algorithm, information indicating that the observed drug dispensation amount is aberrant.


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