Using Machine Learning to Predict Diabetes Complications

Abstract

Diabetes Mellitus (DM) is a chronic disease that is considered to be life threatening. It can affect any part of the body over time, resulting in more serious complications such as Dyslipidemia, Neuropathy and Retinopathy. In this work, different supervised classification algorithms were applied to build several models to predict and diagnose eight diabetes complications. The complications include: Metabolic Syndrome, Dyslipidemia, Neuropathy, Nephropathy, Diabetic Foot, Hypertension, Obesity, and Retinopathy. For this study, a dataset collected by the Rashid Centre for Diabetes and Research (RCDR) located in Ajman, UAE, was utilized. The dataset contains 884 records with 79 features. Some essential preprocessing steps were applied to handle the missing values and unbalanced data problems. Multiple solutions were tested and evaluated.