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:
Dec. 06, 2022

Filed:

Dec. 31, 2019
Applicant:

Cigna Intellectual Property, Inc., Wilmington, DE (US);

Inventors:

Armand E. Prieditis, Arcata, CA (US);

John E. Paton, Raleigh, NC (US);

Assignee:

Cigna Intellectual Property, Inc., Wilmington, DE (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G16H 50/20 (2018.01); G16H 50/30 (2018.01); G06N 20/00 (2019.01); G06F 17/16 (2006.01); G06F 17/18 (2006.01); G16H 40/67 (2018.01);
U.S. Cl.
CPC ...
G16H 50/20 (2018.01); G06F 17/16 (2013.01); G06F 17/18 (2013.01); G06N 20/00 (2019.01); G16H 50/30 (2018.01);
Abstract

A method includes maintaining sets of values for mutable and immutable attributes. Each outcome model of a set of outcome models generates a predicted likelihood of an outcome in response to at least one immutable attribute value and at least one mutable attribute value. A prediction request specifies a first outcome, values for at least one immutable attribute, and values for at least one mutable attribute. The method includes, in response, selecting a group of the sets, where each has values for the immutable attributes that match those of the prediction request. The method includes determining a conditional covariance matrix for the group of sets and then generating a deviation model. The method includes sampling the deviation model to generate sets of mutable attribute values. The method includes, for each of the sets of mutable attribute values, generating, using a selected outcome model, a likelihood of the first outcome occurring.


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