This clinical trial focuses on testing the efficacy of different digital interventions to promote re-engagement in cancer-related long-term follow-up care for adolescent and young adult (AYA) survivors of childhood cancer.
A randomized crossover trial assessing glycemic control using Reinforcement Learning trained Bolus Priming System (BPS_RL) added to the the Automated Insulin Delivery as Adaptive NETwork (AIDANET algorithm) compared to the original AIDANET algorithm.
Safety and Feasibility of a Machine-Learning Bolus Priming Added to Existing Control Algorithm
Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.
| Inclusion Criteria | Exclusion Criteria |
|---|---|
|
|
Sponsor: Sue Brown
These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.