Michael G Brennan

US Patent:

D623355, Sep 7, 2010

Filed:

Aug 22, 2007

Appl. No.:

29/291273

Inventors:

Stuart Harvey Lee - Forest Hills NY, US
Rebecca Jeanne Citron - New York NY, US
Vincent Michael Masotta - Ridgefield CT, US
Liam Anthony Murray - Monroe CT, US
Michael Augustine Brennan - Sandy Hook CT, US
Diane Marie Keenan - Wallingford CT, US

Assignee:

Conopco, Inc. - Englewood Cliffs NJ

International Classification:

2803

US Classification:

D28 63

US Patent:

56175841, Apr 8, 1997

Filed:

Apr 10, 1995

Appl. No.:

8/419198

Inventors:

Michael K. Brennan - Whitestone NY

International Classification:

A42B 318

US Classification:

2206

Abstract:

A multipurpose bandanna-type article comprising an elongated band, a flexible panel and a facility for fastening one edge of the flexible panel to the elongated band.

US Patent:

43325955, Jun 1, 1982

Filed:

Dec 5, 1980

Appl. No.:

6/213428

Inventors:

Sheldon Herbstman - Spring Valley NY
Joseph B. Biasotti - Lagrangeville NY
Michael E. Brennan - Austin TX

Assignee:

Texaco Inc. - White Plains NY

International Classification:

C10L 122

US Classification:

44 72

Abstract:

A detergent additive represented by the formula: R--[O--CH. sub. 2 --CH(CH. sub. 3)]. sub. y --NH--(CH. sub. 2). sub. 3 --NH. sub. 2 in which R is a hydrocarbyl radical having from 8 to 18 carbon atoms and y is about 2 to 6, and a gasoline motor fuel composition containing same.

US Patent:

20200027531, Jan 23, 2020

Filed:

Nov 30, 2018

Appl. No.:

16/205891

Inventors:

- Minnetonka MN, US
Somadev Pasala - Montclair NJ, US
Donald Johnson - Newton NJ, US
Sreedhar Potturi - Bridgewater NJ, US
Dhaval Shah - North Brunswick NJ, US
Anthony Degliomini - Livingston NJ, US
Michael Brennan - Morris Plains NJ, US

International Classification:

G16H 10/60
G06N 20/10
G16H 50/20

Abstract:

A computing entity accesses instances of medical information corresponding to a population of patients and generates a plurality of medical sentences corresponding to the population by, for each patient of the population, generating one medical sentence corresponding to the patient and a timestamp associated with each instance such that the one medical sentence comprises one or more medical codes in a chronological order. The computing entity generates a vector dictionary comprising a plurality of multi-dimensional vectors based on a vector generation model trained using machine learning and the plurality of medical sentences with each multi-dimensional vector corresponding to a medical code. The computing entity generates a digital representation of a first patient of the population using an anagram model and the vector dictionary, determines a health state of the first patient based on the digital representation, and provides an output indicating the health state of the first patient.