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Pediatric Diabetes
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August 17, 2019
Five heterogeneous HbA1c trajectories from childhood to adulthood in youth with type 1 diabetes from three different continents: A group-based modeling approach
Mark A Clements, Anke Schwandt, Kim C Donaghue, et al.
Diabetes Technology & Therapeutics
|
January 6, 2025
Predicting and Ranking Diabetic Ketoacidosis Risk Among Youth with Type 1 Diabetes with a Clinic-to-Clinic Transferrable Machine Learning Model
Craig Vandervelden, Brent Lockee, Mitchell Barnes, et al.
BMJ Open
|
July 9, 2023
Diabetes status and other factors as correlates of risk for thrombotic and thromboembolic events during SARS-CoV-2 infection: A nationwide retrospective case-control study using <i>Cerner Real-World Data™</i>
Erin M Tallon, Mary Pat Gallagher, Vincent S Staggs, et al.
Pediatrics
|
July 28, 2021
Hemoglobin A1c Patterns of Youth With Type 1 Diabetes 10 Years Post Diagnosis From 3 Continents
Jennifer L Sherr, Anke Schwandt, Helen Phelan, et al.
Diabetes Technology & Therapeutics
|
January 19, 2019
State of Type 1 Diabetes Management and Outcomes from the T1D Exchange in 2016-2018
Nicole C Foster, Roy W Beck, Kellee M Miller, et al.
Current Developments in Nutrition
|
April 19, 2024
The Association Between Diet Quality and Glycemic Outcomes Among People with Type 1 Diabetes
Melanie B Gillingham, Martin Chase Marak, Michael C Riddell, et al.
Journal of the American Medical Informatics Association : JAMIA
|
October 9, 2023
Combining uncertainty-aware predictive modeling and a bedtime Smart Snack intervention to prevent nocturnal hypoglycemia in people with type 1 diabetes on multiple daily injections
Clara Mosquera-Lopez, Valentina Roquemen-Echeverri, Nichole S Tyler, et al.
Pediatric Diabetes
|
July 9, 2015
Hemoglobin A1c (HbA1c) changes over time among adolescent and young adult participants in the T1D exchange clinic registry
Mark A Clements, Nicole C Foster, David M Maahs, et al.
JMIR Diabetes
|
May 24, 2023
An "All-Data-on-Hand" Deep Learning Model to Predict Hospitalization for Diabetic Ketoacidosis in Youth With Type 1 Diabetes: Development and Validation Study
David D Williams, Diana Ferro, Colin Mullaney, et al.
Journal of Diabetes Science and Technology
|
October 18, 2025
Establishment of a Diabetes-Tailored Data Intelligence Platform Enhances Clinical Care, Enables Risk-Based Monitoring, and Facilitates Population-Health-Based Approaches at a Pediatric Diabetes Network
Brent Lockee, Craig A Vandervelden, Daniel R Tilden, et al.
Page
of 14
Search research articles
Search
Showing results (101-110 of 134) with videos related to
Sort By:
Page
of 14
Pediatric Diabetes
|
August 17, 2019
Five heterogeneous HbA1c trajectories from childhood to adulthood in youth with type 1 diabetes from three different continents: A group-based modeling approach
Mark A Clements, Anke Schwandt, Kim C Donaghue, et al.
Diabetes Technology & Therapeutics
|
January 6, 2025
Predicting and Ranking Diabetic Ketoacidosis Risk Among Youth with Type 1 Diabetes with a Clinic-to-Clinic Transferrable Machine Learning Model
Craig Vandervelden, Brent Lockee, Mitchell Barnes, et al.
BMJ Open
|
July 9, 2023
Diabetes status and other factors as correlates of risk for thrombotic and thromboembolic events during SARS-CoV-2 infection: A nationwide retrospective case-control study using <i>Cerner Real-World Data™</i>
Erin M Tallon, Mary Pat Gallagher, Vincent S Staggs, et al.
Pediatrics
|
July 28, 2021
Hemoglobin A1c Patterns of Youth With Type 1 Diabetes 10 Years Post Diagnosis From 3 Continents
Jennifer L Sherr, Anke Schwandt, Helen Phelan, et al.
Diabetes Technology & Therapeutics
|
January 19, 2019
State of Type 1 Diabetes Management and Outcomes from the T1D Exchange in 2016-2018
Nicole C Foster, Roy W Beck, Kellee M Miller, et al.
Current Developments in Nutrition
|
April 19, 2024
The Association Between Diet Quality and Glycemic Outcomes Among People with Type 1 Diabetes
Melanie B Gillingham, Martin Chase Marak, Michael C Riddell, et al.
Journal of the American Medical Informatics Association : JAMIA
|
October 9, 2023
Combining uncertainty-aware predictive modeling and a bedtime Smart Snack intervention to prevent nocturnal hypoglycemia in people with type 1 diabetes on multiple daily injections
Clara Mosquera-Lopez, Valentina Roquemen-Echeverri, Nichole S Tyler, et al.
Pediatric Diabetes
|
July 9, 2015
Hemoglobin A1c (HbA1c) changes over time among adolescent and young adult participants in the T1D exchange clinic registry
Mark A Clements, Nicole C Foster, David M Maahs, et al.
JMIR Diabetes
|
May 24, 2023
An "All-Data-on-Hand" Deep Learning Model to Predict Hospitalization for Diabetic Ketoacidosis in Youth With Type 1 Diabetes: Development and Validation Study
David D Williams, Diana Ferro, Colin Mullaney, et al.
Journal of Diabetes Science and Technology
|
October 18, 2025
Establishment of a Diabetes-Tailored Data Intelligence Platform Enhances Clinical Care, Enables Risk-Based Monitoring, and Facilitates Population-Health-Based Approaches at a Pediatric Diabetes Network
Brent Lockee, Craig A Vandervelden, Daniel R Tilden, et al.
Page
of 14