Data, Process, and Data-Driven Representations of Digital Twins in Diabetes: Scoping Review

Background

Diabetes is a chronic metabolic condition characterized by impaired blood glucose regulation. It is often linked to serious health complications and comorbidities that significantly affect quality of life, requiring effective management, continuous monitoring, and advanced data analytics. Notably, tailored diabetes management can be enhanced by digital twins (DTs), which serve as adaptive digital representations of patients, using clinical, physiological, and lifestyle data.

Objective