Abstract
Background: Type 2 diabetes (T2D) is highly heterogeneous with varied patterns of clinical presentation. Machine learning, based on simple parameters, could help to classify T2D with its phenotypes. However, the association between profiled subgroups of T2D and diabetes-related outcomes, such as diabetic retinopathy, has not been outlined.
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