Abstract:
Diabetes is a chronic disease that occurs either when the pancreas does not produce
enough insulin or when the body cannot effectively use the insulin it produces. In 2019,
approximately 463 million adults (20-79 years) were living with diabetes; by 2045 this
will rise to 700 million [1]. With innovation and improvement in data-ware housing,
data mining and emergence of data science as an effective field of utilizing data as a
powerful tool to predict useful information, many studies are being conducted to make
the process affective. In this study Random Forest will be applied on the health
parameters associated with diabetes disease to extract hidden patterns on which
prediction will be done. Diabetes Predictive System (DPS) would be developed to
identify diabetes disease before time on the basics of identified attributes and algorithm.
Hence precautionary measures would be taken eventually. These precautionary
measures will help to decrease the death rate caused by Diabetes
