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. 30, 2025

Filed:

May. 27, 2021
Applicant:

Koninklijke Philips N.v., Eindhoven, NL;

Inventors:

Xin Wang, Belmont, MA (US);

Prescott Peter Klassen, Cambridge, MA (US);

Assignee:

KONINKLIJKE PHILIPS N.V., Eindhoven, NL;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G16H 30/40 (2018.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G16H 15/00 (2018.01); G16H 50/70 (2018.01);
U.S. Cl.
CPC ...
G16H 30/40 (2018.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G16H 15/00 (2018.01); G16H 50/70 (2018.01);
Abstract

A method () of training a machine-learned (ML) image classifier () to classify images () respective to a set of labels includes: generating image-based labels for the images from the set of labels and image-based label confidence values for the image-based labels by applying the ML image classifier to the images; generating report-based labels for the images from the set of labels and report-based label confidence values for the report-based labels by applying a report classifier () to corresponding radiology reports; selecting a training subset of the set of images based on the image-based labels, the report-based labels, the image-based label confidence values, and the report-based label confidence values; assigning a pseudo-label for each image of the training subset which is one of the image-based label or the report-based label for the image; and training the ML image classifier using at least the selected training subset and the assigned pseudo-labels.


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