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. 24, 2024

Filed:

Dec. 16, 2019
Applicant:

Georgia State University Research Foundation, Inc., Atlanta, GA (US);

Inventors:

Sergey Klimov, Roswell, GA (US);

Yi Jiang, Atlanta, GA (US);

Arkadiusz Gertych, El Segundo, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/08 (2023.01); A61B 10/00 (2006.01); G06F 18/243 (2023.01); G06T 7/00 (2017.01); G06T 7/40 (2017.01); G06V 10/20 (2022.01); G06V 10/26 (2022.01); G06V 10/40 (2022.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01);
U.S. Cl.
CPC ...
G06N 3/08 (2013.01); A61B 10/0041 (2013.01); G06F 18/24323 (2023.01); G06T 7/0012 (2013.01); G06T 7/40 (2013.01); G06V 10/20 (2022.01); G06V 10/26 (2022.01); G06V 10/40 (2022.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01); G06T 2207/20084 (2013.01); G06T 2207/30024 (2013.01); G06T 2207/30068 (2013.01); G06V 2201/03 (2022.01);
Abstract

Embodiments of the present systems and methods may provide improved capability to predict the risk of recurrence of ductal carcinoma in situ (DCIS) conditions using whole slide image analysis based on machine learning techniques. For example, in an embodiment, a computer-implemented method for determining treatment of a patient may comprise receiving an image of living tissue of a patient, annotating the entire image into tissue structures, extracting texture features from the annotated image, determining a distribution of the extracted texture features relative to tissue conditions, classifying the patient into a risk group based on the distribution, and treating the patient accordingly based on the risk group.


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