US 12,465,332 B2
Method and system for analyzing intestinal microflora of a subject
Troy Maasland, Delfgauw (NL); and Evgeni Levin, Delfgauw (NL)
Assigned to HORAIZON technology B.V., Delfgauw (NL)
Filed by HORAIZON technology B.V., Delfgauw (NL)
Filed on Sep. 30, 2022, as Appl. No. 17/957,841.
Claims priority of provisional application 63/251,119, filed on Oct. 1, 2021.
Claims priority of application No. 21200561 (EP), filed on Oct. 1, 2021.
Prior Publication US 2023/0104704 A1, Apr. 6, 2023
Int. Cl. A61B 10/00 (2006.01); G06T 7/00 (2017.01); G06V 10/143 (2022.01); G06V 10/40 (2022.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G16B 20/00 (2019.01)
CPC A61B 10/0038 (2013.01) [G06T 7/0012 (2013.01); G06V 10/143 (2022.01); G06V 10/40 (2022.01); G06V 10/764 (2022.01); G06V 10/774 (2022.01); G16B 20/00 (2019.02); G06T 2207/10152 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30092 (2013.01); G06V 2201/03 (2022.01)] 23 Claims
OG exemplary drawing
 
1. A method for analyzing intestinal microflora of a subject, comprising:
receiving, by one or more processors, a digital image of a sample of feces of the subject;
providing the digital image and/or one or more features extracted from the digital image as input to a trained machine learning model which is configured to output a classification based on said input digital image and/or one or more features extracted from the digital image; and
determining, by the one or more processors, data indicative of one or more properties of the intestinal microflora of the subject based on the output image classification,
wherein the machine learning model has been trained using a data set comprising a plurality of digital images of fecal samples, and
wherein each digital image of a fecal sample, of the plurality of digital images of fecal samples, is accompanied by microbial data representative of abundances of predetermined microbial enterotype, species or genera in the fecal sample in the digital image.