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:
Nov. 17, 2020

Filed:

Mar. 11, 2019
Applicant:

Case Western Reserve University, Cleveland, OH (US);

Inventors:

Pranjal Vaidya, Cleveland, OH (US);

Kaustav Bera, Cleveland, OH (US);

Vamsidhar Velcheti, Pepper Pike, OH (US);

Anant Madabhushi, Shaker Heights, OH (US);

Assignee:

Case Western Reserve University, Cleveland, OH (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); G06T 7/11 (2017.01); G06T 7/136 (2017.01); G06K 9/62 (2006.01); G16H 30/40 (2018.01); G06N 20/20 (2019.01); G06N 7/00 (2006.01);
U.S. Cl.
CPC ...
G06T 7/0012 (2013.01); G06K 9/6228 (2013.01); G06K 9/6262 (2013.01); G06N 7/005 (2013.01); G06N 20/20 (2019.01); G06T 7/11 (2017.01); G06T 7/136 (2017.01); G16H 30/40 (2018.01); G06T 2207/10081 (2013.01); G06T 2207/20076 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20152 (2013.01); G06T 2207/30061 (2013.01); G06T 2207/30096 (2013.01);
Abstract

Embodiments access a pre-immunotherapy image of tissue demonstrating NSCLC including a tumor and a peritumoral region; extract a first set of radiomic features from the image; provide the first set of radiomic features to a first machine learning classifier; receive a first probability from the first classifier that the tissue is hyperprogressor (HP) or non-responder (R); if the first probability that the tissue is within a threshold: generate a first classification of the ROT as HP or non-R based on the first probability; if the first probability is not within the threshold: extract a second set of radiomic features from the peritumoral region and provide the second set to a second machine learning classifier; receive a second probability from the second classifier that the tissue is HP or R; generate a second classification of the tissue as HP or R based on the second probability; and display the classification.


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