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:
Sep. 23, 2025

Filed:

Jun. 23, 2021
Applicant:

Cognizant Technology Solutions U.s. Corporation, College Station, TX (US);

Inventors:

Elliot Meyerson, San Francisco, CA (US);

Olivier Francon, Sainte-Foy-lès-Lyon, FR;

Assignee:
Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G16H 50/80 (2018.01); G06N 3/044 (2023.01); G06N 3/045 (2023.01); G06N 3/048 (2023.01); G06N 3/08 (2023.01); G06N 3/086 (2023.01); G06N 5/01 (2023.01); G06N 5/045 (2023.01); G06N 20/10 (2019.01); G06N 20/20 (2019.01); G06Q 30/0204 (2023.01); G06Q 50/26 (2024.01); G16H 40/20 (2018.01); G16H 50/00 (2018.01); G16H 50/20 (2018.01);
U.S. Cl.
CPC ...
G16H 50/80 (2018.01); G06N 3/044 (2023.01); G06N 3/08 (2013.01); G16H 40/20 (2018.01); G16H 50/00 (2018.01); G16H 50/20 (2018.01); G06N 3/045 (2023.01); G06N 3/048 (2023.01); G06N 3/086 (2013.01); G06N 5/01 (2023.01); G06N 5/045 (2013.01); G06N 20/10 (2019.01); G06N 20/20 (2019.01); G06Q 30/0204 (2013.01); G06Q 50/26 (2013.01);
Abstract

The present invention relates to an ESP decision optimization system for epidemiological modeling. ESP based modeling approach is used to predict how non-pharmaceutical interventions (NPIs) affect a given pandemic, and then automatically discover effective NPI strategies as control measures. The ESP decision optimization system comprises of a data-driven predictor, a supervised machine learning model, trained with historical data on how given actions in given contexts led to specific outcomes. The Predictor is then used as a surrogate in order to evolve prescriptor, i.e. neural networks that implement decision policies (i.e. NPIs) resulting in best possible outcomes. Using the data-driven LSTM model as the Predictor, a Prescriptor is evolved in a multi-objective setting to minimize the pandemic impact.


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