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:
Oct. 06, 2026

Filed:

Nov. 07, 2022
Applicants:

GE Precision Healthcare Llc, Wauwatosa, WI (US);

The Trustees of Indiana University, Bloomington, IN (US);

Inventors:

Soumya Ghose, Niskayuna, NY (US);

Zhanpan Zhang, Niskayuna, NY (US);

Sanghee Cho, Niskayuna, NY (US);

Fiona Ginty, Saratoga Springs, NY (US);

Cynthia Elizabeth Landberg Davis, Niskayuna, NY (US);

Jhimli Mitra, Niskayuna, NY (US);

Sunil S. Badve, Indianapolis, IN (US);

Yesim Gokmen-Polar, Noblesville, IN (US);

Elizabeth Mary Mcdonough, Glenville, NY (US);

Assignees:

GE Precision Healthcare LLC, Waukesha, WI (US);

The Trustees of Indiana University, Bloomington, IN (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
A61B 5/00 (2006.01); G06F 18/23213 (2023.01); G06T 7/00 (2017.01); G16H 50/20 (2018.01);
U.S. Cl.
CPC ...
A61B 5/0091 (2013.01); A61B 5/004 (2013.01); A61B 5/4312 (2013.01); A61B 5/7275 (2013.01); A61B 5/742 (2013.01); G06F 18/23213 (2023.01); G06T 7/0012 (2013.01); G16H 50/20 (2018.01); A61B 2576/02 (2013.01); G06T 2207/10116 (2013.01); G06T 2207/30068 (2013.01); G06T 2207/30096 (2013.01); G06V 2201/032 (2022.01);
Abstract

A method for determining a recurrence of a disease in a patient is presented. The method includes generating a plurality of medical images of an organ of the patient and determining a plurality of recurrence probabilities from the plurality of medical images. A recurrence of the disease is determined based on the plurality of recurrence probabilities and clinicopathological data of the patient using a Bayesian network.


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