Curtis Reid Pickering from Woodbridge, CT, age 47

Us Patents

Cancer Biomarkers And Methods Of Use Thereof
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US Patent:

20100003189, Jan 7, 2010
Filed:

Jul 3, 2007
Appl. No.:

12/373047
Inventors:

Thea D. Tlsty - San Francisco CA, US
Hal K. Berman - Toronto, CA
Mona L. Gauthier - Toronto, CA
Bob Y. Liu - San Francisco CA, US
Colleen A. Fordyce - San Francisco CA, US
Curtis R. Pickering - San Francisco CA, US
Paul A. Reynolds - San Francisco CA, US
Nancy Dumont - San Francisco CA, US
Geoffrey M. Benton - San Francisco CA, US
Assignee:

THE REGENTS OF THE UNIVERSITY OF CALIFORNIA - Oakland CA
International Classification:

A61K 51/10
C12Q 1/68
G01N 33/567
A61K 49/00
A61K 51/06
A61K 51/00
A61K 49/14
A61K 49/16
A61K 49/04
A61K 49/06
A61K 49/12
A61P 35/00
US Classification:

424 149, 435 6, 435 721, 424 91, 424 96, 424 173, 424 169, 424 934, 424 935, 424 94, 424 943
Abstract:

Detection methods, assay kits and reagents are provided for detecting pre-cancerous mammary epithelial cell signatures. The disclosed cell signatures comprise a collection of measurements of at least two characteristics of the mammary epithelial cells. Related imaging and diagnostic methods are also disclosed.

Cancer Biomarkers And Methods Of Use Thereof
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US Patent:

20170184601, Jun 29, 2017
Filed:

Oct 3, 2016
Appl. No.:

15/284349
Inventors:

- Oakland CA, US
Hal K. Berman - Toronto, CA
Mona L. Gauthier - Toronto, CA
Bob Y. Liu - San Francisco CA, US
Colleen A. Fordyce - San Francisco CA, US
Curtis R. Pickering - San Francisco CA, US
Paul A. Reynolds - San Francisco CA, US
Nancy Dumont - San Francisco CA, US
Geoffrey M. Benton - San Francisco CA, US
International Classification:

G01N 33/574
Abstract:

The present invention provides detection methods for detecting a pre-cancerous epithelial cell signature. The present invention further provides reagents for use in the detection methods. A subject detection method is useful in various imaging, diagnostic, prognostic, and patient monitoring methods, which are also provided.

Intention Detection In Domain-Specific Information
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US Patent:

20160203118, Jul 14, 2016
Filed:

Mar 16, 2016
Appl. No.:

15/071743
Inventors:

- Armonk NY, US
- Houston TX, US
- Austin TX, US
Lawrence A. Donehower - Houston TX, US
Olivier Lichtarge - Houston TX, US
Sam J. Regenbogen - Houston TX, US
Angela D. Wilkins - Houston TX, US
Curtis R. Pickering - Houston TX, US
Assignee:

International Business Machines Corporation - Armonk NY
Baylor College of Medicine - Houston TX
The Board of Regents, The University of Texas System - Austin TX
International Classification:

G06F 17/27
G06F 17/30
Abstract:

A new information in a language and relating to a subject matter domain is parsed into a constituent set of complete grammatical constructs. In a subset of the complete grammatical constructs, a set of linguistic styles of the language is identified according to a subset of a set of word-style associations related to the language and independent of the subject matter domain. A first weight is assigned to a first linguistic style and a second weight to a second linguistic style from the set of linguistic styles. A first intention information is mapped to the first style using a first style-intention rule, and a second intention information to the second style using a second style-intention rule. A complete grammatical construct in the subset is tagged with the first intention information responsive to a weight associated with the first intention information exceeding an intention selection threshold.

Intention Detection In Domain-Specific Information
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US Patent:

20160162465, Jun 9, 2016
Filed:

Dec 8, 2014
Appl. No.:

14/564068
Inventors:

- Armonk NY, US
- Houston TX, US
- Austin TX, US
Lawrence A. Donehower - Houston TX, US
Olivier Lichtarge - Houston TX, US
Sam J. Regenbogen - Houston TX, US
Angela D. Wilkins - Houston TX, US
Curtis R. Pickering - Houston TX, US
Assignee:

International Business Machines Corporation - Armonk NY
Baylor College of Medicine - Houston TX
The Board of Regents, The University of Texas System - Austin TX
International Classification:

G06F 17/27
G06F 17/28
Abstract:

A new information in a language and relating to a subject matter domain is parsed into a constituent set of complete grammatical constructs. In a subset of the complete grammatical constructs, a set of linguistic styles of the language is identified according to a subset of a set of word-style associations related to the language and independent of the subject matter domain. A first weight is assigned to a first linguistic style and a second weight to a second linguistic style from the set of linguistic styles. A first intention information is mapped to the first style using a first style-intention rule, and a second intention information to the second style using a second style-intention rule. A complete grammatical construct in the subset is tagged with the first intention information responsive to a weight associated with the first intention information exceeding an intention selection threshold.

Event Detection Using Roles And Relationships Of Entities
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US Patent:

20160162788, Jun 9, 2016
Filed:

Dec 8, 2014
Appl. No.:

14/564040
Inventors:

- Armonk NY, US
- Houston TX, US
- Austin TX, US
Meenakshi Nagarajan - San Jose CA, US
William Scott Spangler - San Martin CA, US
Ioana R. Stanoi - Bronx NY, US
Anbu Karani Adikesavan - Houston TX, US
Benjamin J. Bachman - Houston TX, US
Lawrence A. Donehower - Houston TX, US
Olivier Lichtarge - Houston TX, US
Sam J. Regenbogen - Houston TX, US
Angela D. Wilkins - Houston TX, US
Curtis R. Pickering - Houston TX, US
Assignee:

International Business Machines Corporation - Armonk NY
Baylor College of Medicine - Houston TX
The Board of Regents, The University of Texas System - AUSTIN TX
International Classification:

G06N 5/02
G06F 9/54
G06N 99/00
Abstract:

A method, system, and computer program product for event detection using roles and relationships of entities are provided in the illustrative embodiments. A training event and a set of entities participating in the training event are identified in a training data. For a first entity in the set of entities, a first role occupied by the entity in the event is determined. A behavior attribute is assigned to the first role. A relationship of the first role with a second role corresponding to a second entity in the set of entities is determined. An event rule is constructed to detect an event corresponding to the training event in new data and comprising a plurality of roles, behavior attributes, and the relationship. The plurality of roles includes the first role and the second role, and the plurality of behavior attributes includes the behavior attribute assigned to the first role.