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:
Jan. 23, 2024

Filed:

Oct. 27, 2022
Applicant:

Optum Services (Ireland) Limited, Dublin, IE;

Inventors:

David S. Monaghan, Dublin, IE;

Kenneth Bryan, Dublin, IE;

Chirag Chadha, Dublin, IE;

Brian Carter, Dublin, IE;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/62 (2022.01); G16H 50/70 (2018.01); G16B 20/00 (2019.01); G06F 16/18 (2019.01); G06N 20/00 (2019.01); G06F 18/25 (2023.01); G06F 18/24 (2023.01); G06F 18/214 (2023.01);
U.S. Cl.
CPC ...
G16H 50/70 (2018.01); G06F 16/1805 (2019.01); G06F 18/214 (2023.01); G06F 18/24 (2023.01); G06F 18/25 (2023.01); G06N 20/00 (2019.01); G16B 20/00 (2019.02);
Abstract

There is a need for solutions that classification solutions in hierarchical prediction domains. In one embodiment, this need can be addressed by, for example, performing one or more online machine learning, co-occurrence analysis machine learning, structured fusion machine learning, and/or unstructured fusion machine learning. In one particular example, structured predictions inputs are processed in accordance with an online machine learning analysis to generate structurally hierarchical predictions and in accordance with a co-occurrence analysis machine learning analysis to generate structurally non-hierarchical predictions. Then, the structurally hierarchical predictions and the structurally non-hierarchical predictions in accordance with processed by a structured fusion model to generate structure-based predictions. Afterward, the structure-based predictions and non-structure-based predictions can be processed in accordance with an unstructured fusion model to generate one or more unstructured-fused predictions.


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