Models

As part of the DiaClusT project, we developed a multinomial logistic regression classifier to assign patients to distinct type 2 diabetes clusters based on their clinical characteristics. The current approach, including age, sex, BMI, HbA1c, and triglyceride levels, achieved an overall accuracy of 92%, with sensitivity, specificity, and F1-score all exceeding 0.87. The model’s robust performance highlights the potential of incorporating cluster assignment into routine admission workflows, ...