Rising T1DE Alliance: Evidence
Our research
Conference Sessions
Closed-loop, artificial intelligence-based decision support systems and data science
Invited Speaker at the ATTD Yearbook Session at ATTD 2024 (17th International Conference on Advanced Technologies & Treatments for Diabetes)
Florence, Italy
Clements, M
Using digital health technology to prevent and treat diabetes
Invited Speaker at the ATTD Yearbook Session at ATTD 2024 (17th International Conference on Advanced Technologies & Treatments for Diabetes)
Florence, Italy
Clements, M
Just in time adaptive interventions: The new technology to "hack" diabetes self-management behavior
Panel Session ("Self Management of Diabetes" at ATTD 2024 (17th International Conference on Advanced Technologies & Treatments for Diabetes)
Florence, Italy
Clements, M
A high-throughput approach for augmenting rule-based classification of diabetes status and type using Oracle EHR Real-World Data
Panel Session ("Aggregate De-identified EHR Data – Research Using Resources from Two Major EHR Vendors") at AMIA 2023 Annual Symposium
New Orleans, LA, USA
Tallon, EM
Population health management in the digital diabetes era
Invited Speaker Session ("Remote Treatment of Diabetes") at ATTD 2023 (16th International Conference on Advanced Technologies & Treatments for Diabetes)
Berlin, Germany
Clements, M
Deep learning to predict diabetes outcomes
Invited Speaker Session ("Data Science in Diabetes") at ATTD 2023 (16th International Conference on Advanced Technologies & Treatments for Diabetes)
Berlin, Germany
Clements M
Manuscripts and Papers
An “all-data-on-hand” deep learning model to predict hospitalization for diabetic ketoacidosis in youth with Type 1 diabetes: Development and validation study
JMIR Diabetes Volume 8:e47592
Authors: Williams DD, Ferro D, Mullaney C, Skrabonja L, Barnes MS, Patton SR, Lockee B, Tallon EM, Vandervelden CA, Schweisberger C, Mehta S, McDonough R, Lind M, D’Avolio L, Clements MA
Mealtime Insulin BOLUS Score More Strongly Predicts HbA1c Than the Self-Care Inventory in Youth With Type 1 Diabetes
Journal of Diabetes Science and Technology
Authors: Christie J, Clements MA, Williams DD, Cernich J, Patton SR
https://doi.org/10.1177/19322968231192979
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 Cerner Real-World Data™
BMJ Open Volume 13(7)
Authors: Tallon EM, Gallagher MP, Staggs VS, Ferro D, Murthy DB, Ebekozien O, Kosiborod MN, Lind M, Manrique-Acevedo C, Shyu CR, Clements MA
https://doi.org/10.1136/bmjopen-2022-071475
Impact of diabetes status and related factors on COVID-19-associated hospitalization: A nationwide retrospective cohort study of 116,370 adults with SARS-CoV-2 infection
Diabetes Research and Clinical Practice Volume 194:110156
Authors: Tallon EM, Ebekozien O, Sanchez J, Staggs V, Ferro D, McDonough R, Demeterco-Berggren C, Polsky S, Gomez P, Patel N, Prahalad P, Odugbesan O, Mathias P, Lee JM, Smith C, Shyu CR, Clements MA
https://doi.org/10.1016/j.diabres.2022.110156
Other Presentations
Using Artificial Intelligence and Machine Learning to Drive Innovation in Pediatric Care and Quality Improvement
Presenter: Tallon, EM
Pediatric Grand Rounds at BC Children's
Vancouver, BC, Canada 2023
https://ubc.ca.panopto.com/Panopto/Pages/Viewer.aspx?id=980cfd91-c2c5-480b-ba19-b0cb016bf236
Moving from Real-World Data to Real-World Evidence
Presenter: Tallon, EM
Research at Children’s Mercy Month (R@CMM) Lunch ‘n Learn session 2023
Kansas City, MO, USA
Using AI for Personalized Diabetes Care - The Rising T1DE Experience
Presenter: Clements, M
Gainesville, FL, USA
This alliance is led by Children’s Mercy Hospital in collaboration with several multidisciplinary stakeholders.