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:
Jan. 14, 2025

Filed:

May. 12, 2021
Applicants:

Neil Reza Shadbeh Evans, Peoria, IL (US);

Nick Shadbeh Evans, Lynnwood, WA (US);

Inventors:

Neil Reza Shadbeh Evans, Peoria, IL (US);

Nick Shadbeh Evans, Lynnwood, WA (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G16H 50/20 (2018.01); A61B 5/00 (2006.01); A61B 5/0205 (2006.01); A61B 5/021 (2006.01); A61B 5/024 (2006.01); A61B 5/08 (2006.01); A61B 5/083 (2006.01); A61B 5/145 (2006.01); G06N 20/00 (2019.01); G06Q 30/04 (2012.01); G06T 7/00 (2017.01); G16H 10/20 (2018.01); G16H 10/60 (2018.01); G16H 15/00 (2018.01); G16H 30/20 (2018.01); G16H 30/40 (2018.01); G16H 50/50 (2018.01); G16H 50/70 (2018.01);
U.S. Cl.
CPC ...
G16H 50/20 (2018.01); A61B 5/0205 (2013.01); A61B 5/021 (2013.01); A61B 5/024 (2013.01); A61B 5/0816 (2013.01); A61B 5/0836 (2013.01); A61B 5/14542 (2013.01); A61B 5/7267 (2013.01); G06N 20/00 (2019.01); G06Q 30/04 (2013.01); G06T 7/0012 (2013.01); G16H 10/20 (2018.01); G16H 10/60 (2018.01); G16H 15/00 (2018.01); G16H 30/20 (2018.01); G16H 30/40 (2018.01); G16H 50/50 (2018.01); G16H 50/70 (2018.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30048 (2013.01);
Abstract

Systems for preparing, training, and deploying a machine learning algorithm for making medical condition state determinations include at least one processing unit that includes the machine learning algorithm. The at least one processing unit is programmed to receive image input from an imaging device, receive patient health data, encode the patient health data to convert the patient health data to encoded patient health data, and transmit the encoded patient health data into the machine learning algorithm. Systems are configured to make a medical condition state determination based on the image input and the encoded patient health data, via the machine learning algorithm, and provide visual output for the medical condition state determination via a display device such that the visual output may be augmented with the patient health data. Dynamic state information also may be input to the machine learning algorithm and used to make medical condition state determinations.


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