Validation of Insulin Dose Prediction Model Based on Artificial Intelligence Algorithm

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.

NCT Number	NCT07066891
Lead Sponsor	Sun Yat-sen University
Conditions	Diabetes Mellitus, Type 2 Diabetes
Enrollment	400 participants
Start Date	2025-07-15
Primary Completion	2026-06 (estimated)
Study Completion	2026-06 (estimated)
Updated on ClinicalTrials.gov	2025-08-14