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:
Jan. 08, 2019

Filed:

Dec. 19, 2014
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Adam T. Clark, Mantorville, MN (US);

Brian J. Cragun, Rochester, MN (US);

Anthony W. Eichenlaub, Rochester, MN (US);

John E. Petri, St. Charles, MN (US);

John C. Unterholzner, Rochester, MN (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
A61B 5/16 (2006.01); G06N 7/00 (2006.01); G06F 17/27 (2006.01); G06F 17/30 (2006.01); G06F 19/00 (2018.01); G06N 99/00 (2010.01); G10L 15/26 (2006.01); G16H 50/20 (2018.01);
U.S. Cl.
CPC ...
G06F 17/2765 (2013.01); A61B 5/168 (2013.01); G06F 17/30663 (2013.01); G06F 17/30976 (2013.01); G06F 19/00 (2013.01); G06N 7/005 (2013.01); G06N 99/005 (2013.01); G16H 50/20 (2018.01); G10L 15/26 (2013.01);
Abstract

Embodiments herein include a natural language computing system that provides a diagnosis for a participant in the conversation which indicates the likelihood that the participant exhibited a symptom of autism. To provide the diagnosis, the computing system includes a diagnosis system that performs a training process to generate a machine learning model which is then used to evaluate a textual representation of the conversation. For example, the diagnosis system may receive one or more examples of baseline conversations that exhibit symptoms of autisms and those that do not. The diagnosis system may annotate and the baseline conversations and identify features that are used to identify the symptoms of autism. The system generates a machine learning model that weights the features according to whether the identified features are, or are not, an indicator of autism.


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