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:
May. 03, 2022

Filed:

Nov. 30, 2018
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Marwan Sati, Mississauga, CA;

David Richmond, Newton, MA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 20/00 (2019.01); G16H 50/20 (2018.01); G16H 15/00 (2018.01); G16H 30/40 (2018.01); G06F 40/30 (2020.01); G06F 40/205 (2020.01); G06F 40/284 (2020.01);
U.S. Cl.
CPC ...
G16H 50/20 (2018.01); G06F 40/30 (2020.01); G06N 20/00 (2019.01); G16H 15/00 (2018.01); G16H 30/40 (2018.01); G06F 40/205 (2020.01); G06F 40/284 (2020.01);
Abstract

A method, computer system, and a computer program product for automatic labeling to train a machine learning algorithm is provided. The present invention may include labeling a medical image with at least one finding from a corresponding medical report. The present invention may include determining a localization information from the labeled medical image. The present invention may include training the machine learning algorithm with the determined localization information. The present invention may include detecting at least one candidate in a test medical image. The present invention may include generating a discrepancy list between the at least one detected candidate in the test medical image and at least one human-reported finding in a corresponding test medical report. The present invention may include, in response to determining that the generated discrepancy list is above a threshold, retraining the trained machine learning algorithm until the generated discrepancy list is below the threshold.


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