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. 29, 2023

Filed:

Apr. 30, 2020
Applicants:

International Business Machines Corporation, Armonk, NY (US);

Massachusetts Institute of Technology, Cambridge, MA (US);

Inventors:

Uri Kartoun, Cambridge, MA (US);

Kristen Severson, Somerville, MA (US);

Kenney Ng, Arlington, MA (US);

Paul D. Myers, Bloomfield Hills, MI (US);

Wangzhi Dai, Cambridge, MA (US);

Collin M. Stultz, Newton, MA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G16H 40/67 (2018.01); G16H 50/50 (2018.01); G06F 17/18 (2006.01); G16H 50/70 (2018.01); G06F 18/23 (2023.01);
U.S. Cl.
CPC ...
G16H 40/67 (2018.01); G06F 17/18 (2013.01); G06F 18/23 (2023.01); G16H 50/50 (2018.01); G16H 50/70 (2018.01);
Abstract

A computer system selects features of a dataset for predictive modeling. A first set of features that are relevant to outcome are selected from a dataset comprising a plurality of cases and controls. A subset of cases and controls having similar values for the first set of features is identified. The subset is analyzed to select a set of additional features relevant to outcome. A first and second predictive model are evaluated to determine that the second predictive model more accurately predicts outcome, wherein the first predictive model is based on the first set of features and the second predictive model is based on the first set of features and the additional features. The second predictive model is utilized to predict outcomes. Embodiments of the present invention further include a method and program product for selecting features of a dataset for predictive modeling in substantially the same manner described above.


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