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:
Mar. 09, 2021

Filed:

May. 17, 2019
Applicants:

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

The Cleveland Clinic Foundation, Cleveland, OH (US);

Inventors:

Anant Madabhushi, Shaker Heights, OH (US);

Prateek Prasanna, Cleveland, OH (US);

Justis Ehlers, Cleveland, OH (US);

Sunil Srivastava, Cleveland, OH (US);

Assignees:

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

The Cleveland Clinic Foundation, Cleveland, OH (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/46 (2006.01); G06T 7/00 (2017.01); G06K 9/62 (2006.01); G06T 7/32 (2017.01); G06T 7/11 (2017.01); G06T 5/50 (2006.01); G06T 5/20 (2006.01); A61B 3/12 (2006.01); A61B 5/00 (2006.01);
U.S. Cl.
CPC ...
G06T 7/0012 (2013.01); A61B 3/1241 (2013.01); A61B 5/4848 (2013.01); A61B 5/7257 (2013.01); A61B 5/7267 (2013.01); A61B 5/7275 (2013.01); G06K 9/46 (2013.01); G06K 9/628 (2013.01); G06K 9/6262 (2013.01); G06T 5/20 (2013.01); G06T 5/50 (2013.01); G06T 7/11 (2017.01); G06T 7/32 (2017.01); G06K 2209/05 (2013.01); G06T 2207/10064 (2013.01); G06T 2207/20072 (2013.01); G06T 2207/20076 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20224 (2013.01); G06T 2207/30041 (2013.01); G06T 2207/30101 (2013.01);
Abstract

Embodiments facilitate prediction of anti-vascular endothelial growth (anti-VEGF) therapy response in DME patients. A first set of embodiments discussed herein relates to training of a machine learning classifier to determine a prediction for response to anti-VEGF therapy based on a set of graph-network features and a set of morphological features generated based on FA images of tissue demonstrating DME. A second set of embodiments discussed herein relates to determination of a prediction of response to anti-VEGF therapy for a DME patient (e.g., non-rebounder vs. rebounder, response vs. non-response) based on a set of graph-network features and a set of morphological features generated based on FA imagery of the patient.


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