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.

Patent No.:

US 12183462 B1

Date of Patent:

Dec. 31, 2024

Filed:

Apr. 03, 2020

Method for predicting lung cancer development based on artificial intelligence model, and analysis device therefor

Applicant:

Biolink Inc, Daegu, KR;

Inventor:

Hae Won Kim, Daegu, KR;

Assignee:

BIOLINK Inc., Daegu, KR;

Attorney:

PNKIP LLC

Primary Examiner:

Dov Popovici

Int. Cl.

CPC ...

G06V 10/82 (2022.01); A61B 6/03 (2006.01); G06T 7/00 (2017.01); G06V 10/22 (2022.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G16B 20/00 (2019.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G16H 50/70 (2018.01);

U.S. Cl.

CPC ...

G16H 50/20 (2018.01); A61B 6/032 (2013.01); A61B 6/037 (2013.01); G06T 7/0014 (2013.01); G06V 10/22 (2022.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01); G16B 20/00 (2019.02); G16H 30/40 (2018.01); G16H 50/70 (2018.01); G06T 2207/10081 (2013.01); G06T 2207/10104 (2013.01); G06T 2207/20076 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30061 (2013.01); G06V 2201/03 (2022.01);

Abstract

A method for determining a probability of developing lung cancer by using an artificial intelligence model, includes: receiving, by an analysis device, a chest fluorodeoxyglucose (FDG) PET/CT image for a sample; inputting, by the analysis device, the F-18 FDG PET/CT image to a first classification neural network, and outputting prediction information related to development of lung cancer for the sample; and predicting, by the analysis device, a probability of developing lung cancer for the sample on the basis of the prediction information. The first classification neural network is trained by using chest F-18 FDG PET/CT images for healthy people and training images excluding lung cancer regions from chest F-18 FDG PET/CT images for lung cancer patients.

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