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:
Jul. 22, 2025

Filed:

Aug. 03, 2023
Applicant:

Cerner Innovation, Inc., Kansas City, MO (US);

Inventor:

Douglas S. McNair, Leawood, KS (US);

Assignee:

Cerner Innovation, Inc., Kansas City, MO (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G16H 50/20 (2018.01); A61B 5/0205 (2006.01); A61M 25/00 (2006.01); C07K 16/36 (2006.01); C07K 16/44 (2006.01); G06F 18/2413 (2023.01); G16B 20/20 (2019.01);
U.S. Cl.
CPC ...
G16H 50/20 (2018.01); A61B 5/0205 (2013.01); C07K 16/36 (2013.01); G06F 18/2413 (2023.01); G16B 20/20 (2019.02); A61M 25/00 (2013.01); C07K 16/44 (2013.01); C07K 2317/60 (2013.01);
Abstract

Technologies are provided for an improved classifier apparatus and processes for improving the accuracy of classification technology including example applications of such classifiers. A process includes applying clustering to variables contributing to the classification task. The clusters may be represented in a 1-dimensional, 2-dimensional, or 3-dimensional matrix that is a spatial abstraction of the interrelationships. A convolutional transformation may be applied to the matrix so as to reduce the effective dimensionality of the classification problem and improve the signal-to-noise ration. A deep learning neural network method may be applied to the transformed network to generate an improved classification model, which may be utilized by a decision support tool. One embodiment comprises a decision support tool for detecting risk of venous thrombosis and venous thromboembolism (VTE) in a patient, based on phenotype and genomics information.


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