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:

Jul. 05, 2022
Applicant:

Paige.ai, Inc., New York, NY (US);

Inventors:

Supriya Kapur, New York, NY (US);

Ran Godrich, New York, NY (US);

Christopher Kanan, Pittsford, NY (US);

Thomas Fuchs, New York, NY (US);

Leo Grady, Darien, CT (US);

Assignee:

Paige.AI, Inc., New York, NY (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); G06T 7/11 (2017.01); G16H 10/40 (2018.01); G16H 50/20 (2018.01); G16H 30/40 (2018.01); G06V 20/69 (2022.01); G06F 18/214 (2023.01);
U.S. Cl.
CPC ...
G06T 7/0012 (2013.01); G06F 18/214 (2023.01); G06T 7/11 (2017.01); G06V 20/695 (2022.01); G06V 20/698 (2022.01); G16H 10/40 (2018.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G06T 2207/10056 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30024 (2013.01); G06V 2201/03 (2022.01);
Abstract

Systems and methods are disclosed for receiving a target electronic image corresponding to a target specimen, the target specimen comprising a tissue sample of a patient, applying a machine learning system to the target electronic image to identify a region of interest of the target specimen and determine an expression level of, category of, and/or presence of a biomarker in the region of interest, the biomarker comprising at least one from among an epithelial growth factor receptor (EGFR) biomarker and/or a DNA mismatch repair (MMR) deficiency biomarker, the machine learning system having been generated by processing a plurality of training images to predict whether a region of interest is present in the target electronic image, the training images comprising images of human tissue and/or images that are algorithmically generated, and outputting the determined expression level of, category of, and/or presence of the biomarker in the region of interest.


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