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. 21, 2023

Filed:

Mar. 27, 2019
Applicant:

Enlitic, Inc., San Francisco, CA (US);

Inventors:

Kevin Lyman, Fords, NJ (US);

Li Yao, San Francisco, CA (US);

Eric C. Poblenz, Palo Alto, CA (US);

Jordan Prosky, San Francisco, CA (US);

Ben Covington, Berkeley, CA (US);

Anthony Upton, Malvern, AU;

Assignee:

Enlitic, Inc., Fort Collins, CO (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G16H 30/40 (2018.01); G06N 5/04 (2023.01); G16H 50/70 (2018.01); G06Q 10/06 (2023.01); G06T 7/187 (2017.01); G06T 7/44 (2017.01); G06T 7/10 (2017.01); G06T 7/11 (2017.01); G16H 40/20 (2018.01); G16H 10/60 (2018.01); G16H 15/00 (2018.01); G16H 30/20 (2018.01); G16H 50/20 (2018.01); G16H 10/20 (2018.01); G06F 16/245 (2019.01); G06N 20/20 (2019.01); G06N 20/00 (2019.01); G06V 10/25 (2022.01); G06V 10/82 (2022.01); G06V 10/764 (2022.01); G06V 30/19 (2022.01); H04L 67/01 (2022.01); G06F 18/2115 (2023.01); G06F 18/214 (2023.01); G06F 18/2415 (2023.01); G06F 3/0482 (2013.01); G06F 3/0484 (2022.01); G06N 5/045 (2023.01); G06Q 20/14 (2012.01); G06T 3/40 (2006.01); G06T 5/50 (2006.01); G06T 7/12 (2017.01); H04L 67/12 (2022.01); G06T 7/70 (2017.01); G16H 50/30 (2018.01); G06F 40/295 (2020.01); G06V 30/194 (2022.01); G06F 18/24 (2023.01); A61B 5/055 (2006.01); G06Q 50/22 (2018.01); G06Q 10/0631 (2023.01); G06T 5/00 (2006.01); G06T 7/00 (2017.01); G06T 11/00 (2006.01); G06F 9/54 (2006.01); A61B 5/00 (2006.01); G06F 21/62 (2013.01); G06T 11/20 (2006.01); G06F 18/40 (2023.01); G06F 18/21 (2023.01); G06V 40/16 (2022.01); G06V 10/22 (2022.01); A61B 6/03 (2006.01); A61B 8/00 (2006.01); A61B 6/00 (2006.01); G06F 18/2111 (2023.01);
U.S. Cl.
CPC ...
G06Q 10/06315 (2013.01); A61B 5/7264 (2013.01); G06F 3/0482 (2013.01); G06F 3/0484 (2013.01); G06F 9/542 (2013.01); G06F 16/245 (2019.01); G06F 18/214 (2023.01); G06F 18/217 (2023.01); G06F 18/2115 (2023.01); G06F 18/2415 (2023.01); G06F 18/41 (2023.01); G06F 21/6254 (2013.01); G06N 5/04 (2013.01); G06N 5/045 (2013.01); G06N 20/00 (2019.01); G06N 20/20 (2019.01); G06Q 20/14 (2013.01); G06T 3/40 (2013.01); G06T 5/002 (2013.01); G06T 5/008 (2013.01); G06T 5/50 (2013.01); G06T 7/0012 (2013.01); G06T 7/0014 (2013.01); G06T 7/10 (2017.01); G06T 7/11 (2017.01); G06T 7/187 (2017.01); G06T 7/44 (2017.01); G06T 7/97 (2017.01); G06T 11/001 (2013.01); G06T 11/006 (2013.01); G06T 11/206 (2013.01); G06V 10/225 (2022.01); G06V 10/25 (2022.01); G06V 10/764 (2022.01); G06V 10/82 (2022.01); G06V 30/19173 (2022.01); G06V 40/171 (2022.01); 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 40/20 (2018.01); G16H 50/20 (2018.01); H04L 67/01 (2022.05); H04L 67/12 (2013.01); A61B 5/055 (2013.01); A61B 6/032 (2013.01); A61B 6/5217 (2013.01); A61B 8/4416 (2013.01); G06F 18/2111 (2023.01); G06F 18/24 (2023.01); G06F 40/295 (2020.01); G06Q 50/22 (2013.01); G06T 7/70 (2017.01); G06T 2200/24 (2013.01); G06T 2207/10048 (2013.01); G06T 2207/10081 (2013.01); G06T 2207/10088 (2013.01); G06T 2207/10116 (2013.01); G06T 2207/10132 (2013.01); G06T 2207/20076 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30004 (2013.01); G06T 2207/30008 (2013.01); G06T 2207/30016 (2013.01); G06T 2207/30061 (2013.01); G06V 30/194 (2022.01); G06V 2201/03 (2022.01); G16H 50/30 (2018.01); G16H 50/70 (2018.01);
Abstract

A location-based medical scan analysis system is operable to generate a generic model by performing a training step on image data of a plurality of medical scans. Location-based subsets of the plurality of medical scans are generated by including ones of the plurality of medical scans with originating locations that compare favorably to location grouping criteria for the each location-based subset. A plurality of location-based models are generated by performing a fine-tuning step on the generic model, utilizing a corresponding one of the plurality of location-based subsets. Inference data is generated for a new medical scan by utilizing one of the location-based models on the new medical scan, where an originating location associated with the new medical scan compares favorably to location grouping criteria for the location-based subset utilized to generate the location-based model. The inference data is transmitted to a client device for display via a display device.


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