Validation of Insulin Dose Prediction Model Based on Artificial Intelligence Algorithm
Validation of Insulin Dose Prediction Model Based on Long Short- Term Memory Artificial Intelligence Algorithm
Sun Yat-sen University
400 participants
Jul 15, 2025
INTERVENTIONAL
Conditions
Summary
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.
Eligibility
Plain Language Summary
Simplified for easier understanding
This summary was AI-generated to explain the trial in plain language. It is not medical advice. Always discuss eligibility with your doctor before enrolling in a clinical trial.
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Interventions
1. Everyday insulin dosage decided by AI prediction model. 2. CSII treatment continues for 1 to 2 weeks based on whehter or not the patient is newly diagnosed or with different disease duration.
1. Everyday insulin dosage decided by clinicans' experience. 2. CSII treatment continues for 1 to 2 weeks based on whether or not the patient is newly diagnosed or with different disease duration.
Locations(1)
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NCT07066891