Validation of Insulin Dose Prediction Model Based on Artificial Intelligence Algorithm

Recruiting now · Not applicable

Conditions studied: Diabetes Mellitus, Type 2 Diabetes

In brief

The present study aims to conduct a prospective controlled trial comparing an LSTM-based artificial intelligence (AI) prediction model and clinicians' experience in the efficacy and safety of blood glucose control in hospitalized patients with type 2 diabetes mellitus (T2DM) receiving continuous subcutaneous insulin infusion (CSII) treatment in the Department of Endocrinology. The main question it aims to answer is: Is the prediction model superior to or (at least) non-inferior to clinicians' experience? Eligible patients who receive CSII treatment are randomly allocated into the prediction model group and the empirical group. Patients will: 1. Receive CSII treatment as standard of care during hospitalization for 1-2 weeks, where the daily insulin dose regimen is determined by a prediction model or a clinician's experience. 2. Use continuous glucose monitoring (CGM) for glucose tracking. 3. Receive diabetes self-management education covering nutrition and physical activity.

Key facts

Study ID
NCT07066891
Run by
Sun Yat-sen University
People needed
400
Starts
2025-07-15
Expected to finish
2026-06-01
Last updated by the study team
2025-08-14

Who can join

Age: 18 and older, up to 75. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

You may not qualify if…

Where it is running

Full record on ClinicalTrials.gov

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