Diabetes is a chronic ailment characterized by abnormal blood glucose
levels. Diabetes is caused by insufficient insulin synthesis or by cells' insensitivity to
insulin activity. Glucose is essential to health since it is the primary source of energy
for the cells that make up a person's muscles and tissues. On the condition that if a
person has diabetes, his or her body either does not create enough insulin or cannot
utilize the insulin that is produced. When there isn't enough insulin or cells stop
responding to insulin, many dextroses accumulate in the person's vascular framework.
As time passes, this could lead to diseases such as kidney disease, vision loss, and
coronary disease. Although there is no cure for diabetes, losing weight, eating
nutritious foods, being active, and closely monitoring the diabetes level can all assist.
In this research, we used Artificial Neural Network to create a Deep Learning (DL)
model for predicting Diabetes. Then it was validated using an accuracy of 92%. In
addition, with the help of the MIT website, a mobile application was constructed. This
project will now assist in predicting the effects of diabetes and deliver personalized
warnings. Early detection of pre-diabetes can be extremely beneficial to patients since
studies have shown that symptoms of early diabetic difficulties frequently exist at the
time of diagnosis.
Keywords: Accuracy, ANN Algorithm, Deep Learning, Diabetes, Portable Mobile Application.