Early diagnosing diabetes using data mining algorithms

Abstract

Diabetes has become a widespread and long lasting condition that continues to impact an increasing number of individuals across the globe. It is crucial to highlight the significance of accurately identifying, predicting, managing and treating diabetes in order to address this growing concern. Utilizing sophisticated data analysis techniques to examine data relating to diabetes can significantly enhance the early detection and prediction of this ailment, along with its associated complications like low or high blood sugar levels. The findings clearly demonstrate that the decision tree algorithm proves to be the most effective approach in promptly diagnosing diabetes patients and ensuring they receive timely access to suitable treatment options.