joocahyadi/diabetes_classifier_webapp

Diabetes Risk Prediction Classifier

Background

Diabetes mellitus, commonly known as diabetes, is a disease in which the body’s ability to produce or respond to the hormone insulin is impaired, resulting in abnormal metabolism of carbohydrates and elevated levels of glucose in the blood and urine. According to WHO, the number of people with diabetes rose from 108 million in 1980 to 422 million in 2014. This epidemic poses significant challenges to public health systems globally, as diabetes is associated with numerous complications, including cardiovascular disease, kidney failure, blindness, and lower limb amputations. The early detection of diabetes are crucial for preventing its debiliating complications and improving patient conditions.

In this project, a predictive model capable for assesing the likelihood of individual's risk of diabetes has been developed. Leveraging XGBoost, one of the most popular classification algorithm, has shown quite promising result of > 95% accuracy score.