  Diabetes is currently one of the most common, dangerous, and costly diseases
in the world that is caused by an increase in blood sugar or a decrease in
insulin in the body. Diabetes can have detrimental effects on people's health
if diagnosed late. Today, diabetes has become one of the challenges for health
and government officials. Prevention is a priority, and taking care of people's
health without compromising their comfort is an essential need. In this study,
the Ensemble training methodology based on genetic algorithms are used to
accurately diagnose and predict the outcomes of diabetes mellitus. In this
study, we use the experimental data, real data on Indian diabetics on the
University of California website. Current developments in ICT, such as the
Internet of Things, machine learning, and data mining, allow us to provide
health strategies with more intelligent capabilities to accurately predict the
outcomes of the disease in daily life and the hospital and prevent the
progression of this disease and its many complications. The results show the
high performance of the proposed method in diagnosing the disease, which has
reached 98.8%, and 99% accuracy in this study.
