Using an AI-Based Multimodal Model to Detect Early Cognitive Impairment in Adults Aged 40 to 75 with Type 2 Diabetes

What this Trial Is About

Researchers are evaluating an artificial intelligence-based multimodal cognitive screening system to identify mild cognitive impairment MCI related to diabetes early in patients with type 2 diabetes mellitus T2DM. This observational study follows participants for 3 to 5 years to assess the systems accuracy and feasibility. The study also explores how diabetic metabolic indicators, such as glycemic variability and HbA1c levels, relate to changes in cognitive function, aiming to improve early detection and intervention for cognitive decline in T2DM patients. Participants are observed without additional interventions over the 3 to 5 years of follow-up. The study includes groups of participants with normal cognition and those with mild cognitive impairment. Cognitive status data are collected at the beginning and end of the study period, with no study drug or treatment administered. During the study, participants undergo cognitive assessments and monitoring of diabetic metabolic factors. Researchers measure the accuracy of the AI screening system in early detection and track the rate of cognitive decline over the follow-up period. The study also evaluates the predictive value of combining multiple types of data. Participants remain under observation with regular assessments, helping to understand the relationship between diabetes and cognitive changes over time.

The Application of an AI-driven Multimodal Predictive Model for Cognitive Impairment in Patients With Type 2 Diabetes Mellitus