Diabetes
Conditions
Brief summary
Constructing an intelligent insulin decision-making system for dynamic glucose control in type 2 diabetes mellitus via a multicentre federated learning algorithm, comparing the performance of the federated learning model, the local model and the initial model, and evaluating their feasibility and safety.
Detailed description
Constructing an intelligent insulin decision-making system for dynamic glucose control in type 2 diabetes mellitus via a multicentre federated learning algorithm, comparing the performance of the federated learning model, the local model and the initial model, and evaluating their feasibility and safety.
Interventions
OTHERpatient record
using patient record to construct AI models
Sponsors
Shanghai Zhongshan Hospital
Study design
Observational model
OTHER
Time perspective
OTHER
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* type 2 diabetes inpatients receiving insulin therapy
Exclusion criteria
* use of insulin pumps or glucocorticoids during hospitalisation * less than two days of insulin therapy
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| the accuracy of AI models | up to 2 years |
Contacts
Primary ContactXiaoying Li, PhD.
Backup ContactYing Chen
Outcome results
None listed