Diabetes Prediction Using Data Science

Diabetes prediction in Data Science

Abstract:

The emerging increase of diabetes in across world, that recently affects around million people at worldwide, of which extra than one-third go undetected in near the beginning stage, a strong need for supporting the health check decision-making process is generated in diabetes. A huge numbers of researches have focused either in using one of the algorithms or in the comparisons of the performances of algorithms on a given, usually predefined datasets that are accessible. To focus on the joint implementation of the support vector machine (SVM) and Naive Bayes statistical modeling, in the dataset acquired from the medical examinations of patients, in order to improve the computer-supported diagnosis reliability. The dataset contains some attributes that have not been previously used in computer-based evaluations. The results show that the joint implementation of two algorithms improves significantly the overall reliability of the system outcome, which is crucial in the computer-supported diabetes diagnostic process.