Predictive Analysis of Type-1 and Type-2 Diabetes Mellitus Using Machine Learning

Abstract

The health care domain is important to the field where the prediction and classification of value. The health care problem recognizes by WHO is that the world suffers from diabetics. Health care domain is a very hues volume of data needs to be handle very carefully and confidentially, various machine learning technique to examine the data, this data provides useful knowledge if the certain data mining technique is applied to this kind of data. Health care professionals are required to reliable prediction system to diagnose diabetes. In the health care domain, accuracy and efficiency are more important, so using the various classification technique and algorithmic strategies to address the problems efficiently. The major problem, making an attempt to increases the accuracy of the prediction, the framework most robust, and more than one dataset. This paper systematically identifies the elements such as a diabetes type, major contribution, and the strength of the approach. This study on advances in machine learning that have had a substantial impact on the revealing and conclusion with respect to diabetes mellitus.

Note: Funding statement: none; Declaration of interests: none

Keywords: Type-1 Diabetes, Type-2 Diabetes, Insulin, Machine Learning, Prediction

JEL Classification: C67, C02