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:
Jun. 20, 2023

Filed:

Jun. 08, 2020
Applicant:

Cornell University, Ithaca, NY (US);

Inventors:

Mahsa Shoaran, Ithaca, NY (US);

Milad Taghavi, Ithaca, NY (US);

Benyamin Haghi, Ithaca, NY (US);

Masoud Farivar, Ithaca, NY (US);

Azita Emami, Ithaca, NY (US);

Assignees:

CORNELL UNIVERSITY, Ithaca, NY (US);

CALIFORNIA INSTITUTE OF TECHNOLOGY, Pasadena, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G16H 50/20 (2018.01); G16H 50/30 (2018.01); G16H 40/67 (2018.01); G06N 20/20 (2019.01); G06N 5/04 (2023.01); A61B 5/00 (2006.01); G06N 5/01 (2023.01); A61B 5/11 (2006.01); G16H 10/60 (2018.01); G16H 50/70 (2018.01);
U.S. Cl.
CPC ...
G16H 50/20 (2018.01); A61B 5/725 (2013.01); A61B 5/7264 (2013.01); A61B 5/7275 (2013.01); G06N 5/01 (2023.01); G06N 5/04 (2013.01); G06N 20/20 (2019.01); G16H 40/67 (2018.01); G16H 50/30 (2018.01); A61B 5/1101 (2013.01); A61B 5/4082 (2013.01); A61B 5/4094 (2013.01); G16H 10/60 (2018.01); G16H 50/70 (2018.01);
Abstract

Methods, systems, and devices are disclosed for an efficient hardware architecture to implement gradient boosted trees for detecting biological conditions. For example, a method of detecting a biological condition includes receiving, by a device, a plurality of physiological signals from a plurality of input channels of the device, selecting, based on a trained prediction model, one or more input channels from the plurality of input channels, converting the one or more physiological signals received from the one or more input channels to one or more digital physiological signals, identifying, by using the plurality of gradient boosted decision trees, the selected characteristic in the one or more digital physiological signals, and determining a presence of a physiological condition based on an addition of the output values obtained from the plurality of gradient boosted decision trees.


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