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.
Patent No.:
Date of Patent:
Jul. 23, 2024
Filed:
Jul. 22, 2021
Applicant:
Iterative Scopes, Inc., Cambridge, MA (US);
Inventors:
Jonathan Ng, Cambridge, MA (US);
Jean-Pierre Schott, Weston, MA (US);
Daniel Wang, Cambridge, MA (US);
Assignee:
Iterative Scopes, Inc., Cambridge, MA (US);
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G16H 50/20 (2018.01); A61B 1/31 (2006.01); A61B 5/00 (2006.01); G06F 18/21 (2023.01); G06F 18/24 (2023.01); G06N 3/08 (2023.01); G06T 7/00 (2017.01); G16B 20/00 (2019.01); G16B 30/00 (2019.01); G16B 40/20 (2019.01); G16H 10/60 (2018.01); G16H 30/20 (2018.01); G16H 30/40 (2018.01); G16H 50/30 (2018.01); G16H 50/50 (2018.01); G16H 50/70 (2018.01); G16H 70/60 (2018.01); G16H 10/20 (2018.01); G16H 10/40 (2018.01);
U.S. Cl.
CPC ...
G16H 50/20 (2018.01); A61B 1/31 (2013.01); A61B 5/7267 (2013.01); A61B 5/7275 (2013.01); G06F 18/21 (2023.01); G06F 18/24 (2023.01); G06N 3/08 (2013.01); G06T 7/0012 (2013.01); G16B 20/00 (2019.02); G16B 30/00 (2019.02); G16B 40/20 (2019.02); G16H 10/60 (2018.01); G16H 30/20 (2018.01); G16H 30/40 (2018.01); G16H 50/30 (2018.01); G16H 50/50 (2018.01); G16H 50/70 (2018.01); G16H 70/60 (2018.01); G06T 2207/10068 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30092 (2013.01); G06V 2201/03 (2022.01); G16H 10/20 (2018.01); G16H 10/40 (2018.01);
Abstract
This specification describes systems and methods for obtaining various patient related data for inflammatory bowel disease (IBD). The methods and systems are configured for using machine learning to determine measurements of various characteristics and provide analysis related to IBD. The methods and systems may also obtain and incorporate electronic health data as well as other relevant data of patients along with endoscopic data to use for prediction IDB progression and recommending treatment.