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. 20, 2022

Filed:

Oct. 03, 2018
Applicant:

Koninklijke Philips N.v., Eindhoven, NL;

Inventors:

Vijayananda Jagannatha, Bangalore, IN;

Vinay Pandit, Gokarn, IN;

Srinivas Prasad Madapusi Raghavan, Bangalore, IN;

Rupesh Vakkachi Kandi, Kozhikode, IN;

Assignee:

KONINKLIJKE PHILIPS N.V., Eindhoven, NL;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 9/44 (2018.01); G06F 9/455 (2018.01); H04N 7/14 (2006.01); H04N 7/15 (2006.01); G16H 30/40 (2018.01); G06F 16/22 (2019.01); G06F 11/36 (2006.01); G06N 3/04 (2006.01); G06N 3/08 (2006.01); G06N 7/00 (2006.01); G06Q 10/06 (2012.01); G16H 40/40 (2018.01);
U.S. Cl.
CPC ...
G16H 30/40 (2018.01); G06F 11/3688 (2013.01); G06F 16/2246 (2019.01); G06N 3/0445 (2013.01); G06N 3/0454 (2013.01); G06N 3/08 (2013.01); G06N 7/005 (2013.01); G06Q 10/0633 (2013.01); G16H 40/40 (2018.01);
Abstract

Systems and methods are disclosed for generating device test cases for medical imaging devices, which are not only reflective of current actual field usage of the device but also provide outlook on future usage. A probabilistic model of usage patterns is generated from historic data present in the device field logs by mining the current usage patterns. A Deep Long Short Term Memory Neural Network model of the usage patterns is constructed to predict the future usage patterns. Additionally, to capture the changing trends of device usage patterns in the field, predictive models are continuously updated in real time, and the test cases generated log files by the models are integrated into an automated testing system.


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