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

NCT06434623 | Not Yet Recruiting FDA Drug

• 1 other identifier: 20240324025304420
• Study Type: observational
• Target: 30,100
• Locations: 0 countries
• Sites: N/A

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.

Conditions

Diabetes

Outcome Measures

Primary Outcomes (1)

• the accuracy of AI models

  up to 2 years

Study Arms (1)

patients record

Other: patient record

Interventions

patient record OTHER

using patient record to construct AI models

patients record

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

type 2 diabetes who

You may qualify if:

• type 2 diabetes inpatients receiving insulin therapy

You may not qualify if:

• use of insulin pumps or glucocorticoids during hospitalisation
• less than two days of insulin therapy

Sponsors & Collaborators

• Shanghai Zhongshan Hospital: lead

MeSH Terms

Conditions

Diabetes Mellitus

Interventions

Medical Records

Condition Hierarchy (Ancestors)

Glucose Metabolism Disorders; Metabolic Diseases; Nutritional and Metabolic Diseases; Endocrine System Diseases

Intervention Hierarchy (Ancestors)

Records; Data Collection; Epidemiologic Methods; Investigative Techniques; Organization and Administration; Health Services Administration; Health Care Evaluation Mechanisms; Quality of Health Care; Health Care Quality, Access, and Evaluation; Public Health; Environment and Public Health

Study Officials

• Xiaoying Li, Professor

  Fudan University

  STUDY DIRECTOR

Central Study Contacts

Xiaoying Li, PhD.

CONTACT

02164041990; li.xiaoying@zs-hospital.sh.cn

Ying Chen

CONTACT

13482; chen.ying4@zs-hospital.sh.cn

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: OTHER
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: May 23, 2024
• First Posted: May 30, 2024
• Study Start: September 1, 2024
• Primary Completion (Estimated): June 1, 2026
• Study Completion (Estimated): June 30, 2026
• Last Updated: July 16, 2024

Record last verified: 2024-05