Diabetes is a significant health concern with more than 30 million Americans living with diabetes. Onset of diabetes increases the risk for various complications, including kidney disease, myocardial infractions, heart failure, stroke, retinopathy, and liver disease. In this paper, we study and predict the onset of these complications using a network-based approach by identifying fast and slow progressors. That is, given a patient's diagnosis of diabetes, we predict the likelihood of developing one or more of the possible complications, and which patients will develop complications quickly. This combination of "if a complication will be developed" with "how fast it will be developed" can aid the physician in developing better diabetes management program for a given patient.
Keywords: Diabetes; Disease network; Disease prediction; Heart failure; Kidney disease; Liver disease; Myocardial infarction; Real-world data; Retinopathy.