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. 01, 2026

Filed:

Mar. 30, 2022
Applicant:

Hoffmann-la Roche Inc., Little Falls, NJ (US);

Inventors:

Ido Ben Shaul, Raanana, IL;

Jacob Gildenblat, Holon, IL;

Eldad Klaiman, Starnberg, DE;

Assignee:

Hoffmann-La Roche Inc., Little Falls, NJ (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G16H 50/70 (2018.01); G06T 7/00 (2017.01); G06V 10/44 (2022.01); G06V 10/764 (2022.01); G06V 10/77 (2022.01); G06V 10/82 (2022.01); G06V 20/69 (2022.01); G16H 30/20 (2018.01); G16H 50/20 (2018.01); G06N 3/084 (2023.01);
U.S. Cl.
CPC ...
G16H 50/70 (2018.01); G06T 7/0012 (2013.01); G06V 10/454 (2022.01); G06V 10/764 (2022.01); G06V 10/7715 (2022.01); G06V 10/82 (2022.01); G06V 20/695 (2022.01); G06V 20/698 (2022.01); G16H 30/20 (2018.01); G16H 50/20 (2018.01); G06N 3/084 (2013.01); G06T 2200/24 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30024 (2013.01);
Abstract

The method includes, for each of a plurality of tiles of an image, extracting a feature vector from the tile; providing a Multiple-Instance-Learning program configured to use a model for classifying any input image as a member of one out of at least two different classes based on feature vectors extracted from the tiles; for each of the tiles, computing a certainty value indicating the certainty of the model regarding the contribution of the tile's feature vector on the classification of the image; for each of the images, using, by the MIL-program, a certainty-value-based pooling function for aggregating the feature vectors of the image or predictive values computed from the feature vectors of the image into an aggregated predictive value as a function of the certainty values of the tiles; and classifying each of the images as a member of one of the classes based on the aggregated predictive value.


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