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Diabetes Technology & Therapeutics
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April 15, 2011
Using a multi-level B-spline model to analyze and compare patient glucose profiles based on continuous monitoring data
Hui Zheng, David M Nathan, David A Schoenfeld
Science Translational Medicine
|
October 7, 2016
Mechanistic modeling of hemoglobin glycation and red blood cell kinetics enables personalized diabetes monitoring
Roy Malka, David M Nathan, John M Higgins
Diabetes Care
|
December 24, 2004
Biological variation in HbA1c predicts risk of retinopathy and nephropathy in type 1 diabetes: response to McCarter et al
Saul Genuth, John M Lachin, David M Nathan
The Journal of Clinical Endocrinology and Metabolism
|
January 26, 2006
Insulin sensitivity during combined androgen blockade for prostate cancer
Matthew R Smith, Hang Lee, David M Nathan
The New England Journal of Medicine
|
July 13, 2017
Frequency of Evidence-Based Screening for Diabetic Retinopathy
David M Nathan, Ionut Bebu, John M Lachin
Diabetes Care
|
August 12, 2021
The Beneficial Effects of Earlier Versus Later Implementation of Intensive Therapy in Type 1 Diabetes
John M Lachin, Ionut Bebu, David M Nathan, et al.
Diabetes Research and Clinical Practice
|
April 21, 2018
Estimating HbA1c from timed Self-Monitored Blood Glucose values
WuQiang Fan, Hui Zheng, Nancy Wei, et al.
Clinical Chemistry
|
December 4, 2010
Gaps in the glycation gap hypothesis
David B Sacks, David M Nathan, John M Lachin
Journal of the American Dietetic Association
|
May 2, 2006
Psychological predictors of physical activity in the diabetes prevention program
Linda M Delahanty, Molly B Conroy, David M Nathan, et al.
Diabetes Care
|
December 21, 2013
Update on cardiovascular outcomes at 30 years of the diabetes control and complications trial/epidemiology of diabetes interventions and complications study
John M Lachin, Trevor J Orchard, David M Nathan, et al.
Page
of 25
Search research articles
Search
Showing results (41-50 of 245) with videos related to
Sort By:
Page
of 25
Diabetes Technology & Therapeutics
|
April 15, 2011
Using a multi-level B-spline model to analyze and compare patient glucose profiles based on continuous monitoring data
Hui Zheng, David M Nathan, David A Schoenfeld
Science Translational Medicine
|
October 7, 2016
Mechanistic modeling of hemoglobin glycation and red blood cell kinetics enables personalized diabetes monitoring
Roy Malka, David M Nathan, John M Higgins
Diabetes Care
|
December 24, 2004
Biological variation in HbA1c predicts risk of retinopathy and nephropathy in type 1 diabetes: response to McCarter et al
Saul Genuth, John M Lachin, David M Nathan
The Journal of Clinical Endocrinology and Metabolism
|
January 26, 2006
Insulin sensitivity during combined androgen blockade for prostate cancer
Matthew R Smith, Hang Lee, David M Nathan
The New England Journal of Medicine
|
July 13, 2017
Frequency of Evidence-Based Screening for Diabetic Retinopathy
David M Nathan, Ionut Bebu, John M Lachin
Diabetes Care
|
August 12, 2021
The Beneficial Effects of Earlier Versus Later Implementation of Intensive Therapy in Type 1 Diabetes
John M Lachin, Ionut Bebu, David M Nathan, et al.
Diabetes Research and Clinical Practice
|
April 21, 2018
Estimating HbA1c from timed Self-Monitored Blood Glucose values
WuQiang Fan, Hui Zheng, Nancy Wei, et al.
Clinical Chemistry
|
December 4, 2010
Gaps in the glycation gap hypothesis
David B Sacks, David M Nathan, John M Lachin
Journal of the American Dietetic Association
|
May 2, 2006
Psychological predictors of physical activity in the diabetes prevention program
Linda M Delahanty, Molly B Conroy, David M Nathan, et al.
Diabetes Care
|
December 21, 2013
Update on cardiovascular outcomes at 30 years of the diabetes control and complications trial/epidemiology of diabetes interventions and complications study
John M Lachin, Trevor J Orchard, David M Nathan, et al.
Page
of 25