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. 10, 2022

Filed:

Feb. 15, 2019
Applicant:

Babylon Partners Limited, London, GB;

Inventors:

Laura Helen Douglas, London, GB;

Pavel Myshkov, London, GB;

Robert Walecki, London, GB;

Iliyan Radev Zarov, London, GB;

Konstantinos Gourgoulias, London, GB;

Christopher Lucas, London, GB;

Christopher Robert Hart, London, GB;

Adam Philip Baker, London, GB;

Maneesh Sahani, London, GB;

Iurii Perov, London, GB;

Saurabh Johri, London, GB;

Assignee:
Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06N 7/00 (2006.01); G16H 50/20 (2018.01); G16H 50/70 (2018.01); G06N 3/04 (2006.01); G16H 50/30 (2018.01); G06N 20/20 (2019.01); G06F 17/16 (2006.01); G06N 3/08 (2006.01); G06N 5/04 (2006.01); G16B 45/00 (2019.01); G16B 5/20 (2019.01); G16H 50/50 (2018.01);
U.S. Cl.
CPC ...
G06N 7/005 (2013.01); G06F 17/16 (2013.01); G06N 3/0454 (2013.01); G06N 3/08 (2013.01); G06N 5/04 (2013.01); G06N 20/20 (2019.01); G16B 5/20 (2019.02); G16B 45/00 (2019.02); G16H 50/20 (2018.01); G16H 50/30 (2018.01); G16H 50/70 (2018.01); G06N 3/082 (2013.01); G16H 50/50 (2018.01);
Abstract

Methods for providing a computer implemented medical diagnosis are provided. In one aspect, a method includes receiving an input from a user comprising at least one symptom of the user, and providing the at least one symptom as an input to a medical model. The method also includes deriving estimates of the probability of the user having a disease from the discriminative model, inputting the estimates to the inference engine, performing approximate inference on the probabilistic graphical model to obtain a prediction of the probability that the user has that disease, and outputting the probability of the user having the disease for display by a display device.


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