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

NCT06434623 · Status: NOT_YET_RECRUITING · Type: OBSERVATIONAL · Enrollment: 30100

Last updated 2024-07-16

No results posted yet for this study

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

Interventions

OTHER

patient record

using patient record to construct AI models

Sponsors & Collaborators

  • Shanghai Zhongshan Hospital

    lead OTHER

Principal Investigators

  • Xiaoying Li, Professor · Fudan University

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2024-09-01
Primary Completion
2026-06-01
Completion
2026-06-30
FDA Drug
Yes

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06434623 on ClinicalTrials.gov