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

NCT ID: NCT06434623

Last Updated: 2024-07-16

Basic Information

• Recruitment Status: NOT_YET_RECRUITING
• Total Enrollment: 30100 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2024-09-01
• Study Completion Date: 2026-06-30

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.

Conditions

Diabetes

Study Design

• Observational Model Type: OTHER
• Study Time Perspective: OTHER

Study Groups

patients record

patient record

Intervention Type: OTHER

using patient record to construct AI models

Interventions

patient record

using patient record to construct AI models

Intervention Type: OTHER

Eligibility Criteria

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

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Shanghai Zhongshan Hospital

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Xiaoying Li, Professor

Role: STUDY_DIRECTOR

Fudan University

Central Contacts

Xiaoying Li, PhD.

Role: CONTACT

li.xiaoying@zs-hospital.sh.cn

02164041990

Ying Chen

Role: CONTACT

chen.ying4@zs-hospital.sh.cn

13482

Other Identifiers

20240324025304420

Identifier Type: -

Identifier Source: org_study_id