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Osman M Qamar, 51Wilton, CT

Osman Qamar Phones & Addresses

Wilton, CT   

1871 Eclipse St, Upland, CA 91784    909-9206061   

Cambridge, MA   

Rancho Cucamonga, CA   

Pasadena, CA   

San Dimas, CA   

Westlake Village, CA   

Los Angeles, CA   

1871 Eclipse Way, Upland, CA 91784    909-9206061   

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Osman M Qamar

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Work

Company: Innoventz, corporation Feb 2004 Position: Senior consultant/founder

Education

School / High School: University of Southern California Specialities: Clinical Data Management

Emails

Industries

Real Estate

Mentions for Osman M Qamar

Osman Qamar resumes & CV records

Resumes

Osman Qamar Photo 11

Sales At Aim168 Real Estate

Location:
United States
Industry:
Real Estate
Osman Qamar Photo 12

Osman Qamar - Rancho Cucamonga, CA

Work:
Innoventz, Corporation Feb 2004 to 2000
Senior Consultant/Founder
Innoventz, Corporation Jul 2013 to Feb 2014 Innoventz, Corporation Jan 2013 to Jun 2013 Innoventz, Corporation Dec 2011 to Dec 2012 Innoventz, Corporation Nov 2009 to Nov 2011 Innoventz, Corporation Oct 2008 to Oct 2009 Innoventz, Corporation Jan 2008 to Sep 2008
Software Development
Innoventz, Corporation Jan 2007 to Dec 2007 Innoventz, Corporation - Rancho Cucamonga, CA Feb 2004 to Dec 2006
Education:
University of Southern California
Clinical Data Management
University of Southern California 1995
Master of Science in Biomedical Engineering
University of Southern California 1993
Bachelor of Science in Biomedical Engineering

Publications & IP owners

Us Patents

System And Method For Medical Evaluation And Monitoring

US Patent:
2008007, Mar 20, 2008
Filed:
Sep 12, 2007
Appl. No.:
11/900464
Inventors:
Alan Marcus - Laguna Niguel CA, US
John Shin - La Canada CA, US
Brenda Perry - Newbury Park CA, US
Julie Brooke - Moorpark CA, US
Osman Qamar - Upland CA, US
International Classification:
G06F 19/00
US Classification:
705003000
Abstract:
A diabetes data management system (DDMS) and corresponding method assist a health-care professional in monitoring and evaluating the progress of a diabetic patient by generating various types of reports that are indicative of periodic trends in the patient's behavior, including compliance with a prescribed course of therapy. Specifically, input data, including carbohydrate, insulin, and glucose data are uploaded by the patient into the DDMS, which then generates periodic (e.g., weekly), patient-specific output data in the form of box plot graphs, bar graphs, etc. over an extended period of time (e.g., several months). By studying the trends indicated by the output data, the health-care professional can modify the patient's therapy in accordance with a set of goals for that patient. Output data may include insulin delivery effectiveness, bolus/basal delivery effectiveness, carbohydrate intake, usage of bolus wizard, bolus wizard compliance, Glucose alert response, frequency of infusion set replacement, and sensor usage.

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