Development and external validation of an algorithm for self‐identification of risk for microvascular complications in patients with type 1 diabetes

Microvascular complications, such as diabetic retinopathy (DR), diabetic nephropathy (DN) and diabetic peripheral neuropathy (DPN), are common and serious outcomes of inadequately managed type 1 diabetes (T1D). Timely detection and intervention in these complications are crucial for improving patient outcomes. This study aimed to develop and externally validate machine learning (ML) models for self-identification of microvascular complication risks in T1D population.