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:
Sep. 04, 2018

Filed:

Jun. 01, 2016
Applicant:

Grand Rounds, Inc., San Francisco, CA (US);

Inventors:

Seiji James Yamamoto, San Francisco, CA (US);

Ranjit Chacko, San Francisco, CA (US);

Assignee:

GRAND ROUNDS, INC., San Francisco, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 19/00 (2018.01); G06F 17/30 (2006.01); G16H 40/20 (2018.01); G16H 50/20 (2018.01); G06Q 50/22 (2018.01); G06Q 10/10 (2012.01);
U.S. Cl.
CPC ...
G16H 40/20 (2018.01); G06F 17/30598 (2013.01); G06F 17/30958 (2013.01); G06F 19/327 (2013.01); G06F 19/328 (2013.01); G06F 19/345 (2013.01); G16H 50/20 (2018.01); G06F 17/3071 (2013.01); G06Q 10/10 (2013.01); G06Q 50/22 (2013.01);
Abstract

Systems and methods are provided for data driven analysis, modeling, and semi-supervised machine learning for qualitative and quantitative determinations. The systems and methods include obtaining data associated with individuals, and determining features associated with the individuals based on the data and similarities among the individuals based on the features. The systems and methods can label some individuals as exemplary, generate a graph wherein nodes of the graph represent individuals, edges of the graph represent similarity among the individuals, and nodes associated labeled individuals are weighted. The disclosed system and methods can apply a weight to unweighted nodes of the graph based on propagating the labels through the graph where the propagation is based on influence exerted by the weighted nodes on the unweighted nodes. The disclosed systems and methods can provide output associated with the individuals represented on the graph and the associated weights.


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