Data Mining Techniques in Diabetes Prediction and Diagnosis: A Review

Diabetes Mellitus is a major disorder of metabolism. According to WHO, it has been listed among the world's top 10 deadliest diseases. Diagnosing and Treating diabetes is often effortful and critical. For the early prediction of the disease and thereby avert numerous other consequences, various data mining tools can be put to use. Studies have been conducted and undergoing using several potential approaches in this area to enhance the prognosis and diagnosis of Diabetes Mellitus. This paper provides a complete systematic review of data mining-based prediction of diabetes mellitus. The objective is to review studies that implemented various analytical methods that are being used in this field and also to compare them based on the predictive accuracy that is yielded. In addition to that, this research study has been planned to address some challenges and propose a future model, which should be considered based on the comparative analysis.