NCT06434623

Federal Learning Algorithm for an Intelligent Insulin Decision System for Dynamic Glucose Control in Type 2 Diabetic Patients

A Multicenter Federal Learning Algorithm to Build an Intelligent Insulin Decision System for Dynamic Glucose Control in Type 2 Diabetic Patients

• Status: Not Yet Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 30,100 (estimated)
• Sponsor: Shanghai Zhongshan Hospital · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

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.

Conditions

• Diabetes

Interventions

Type	Name	Description
OTHER	patient record	using patient record to construct AI models

Timeline

• Start date: 2024-09-01
• Primary completion: 2026-06-01
• Completion: 2026-06-30
• First posted: 2024-05-30
• Last updated: 2024-07-16

Regulatory

• FDA-regulated drug study