Open AccessPredict Diabetes Mellitus Using Machine Learning Algorithms
Author(s) -
Bano Farhana,
K Munidhanalakshmi,
R. Madana Mohana
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2089/1/012002
Subject(s) - diabetes mellitus , logistic regression , medicine , machine learning , blood sugar , artificial intelligence , decision tree , disease , algorithm , correctness , computer science , endocrinology
Diabetes mellitus has become a very frequent disease that affects totally different organs of human body. Diabetes cause diverge depending on genetic, family history, health and environmental factors. Diabetes mellitus refers to a gaggle of diseases that affect how your body uses blood glucose. The underlying reason behind diabetes varies by type. But, despite what kind of diabetes you’ve got, it will cause excess sugar in your blood. Diabetes will be of two types, they are Type1 Diabetes and Type2 Diabetes. Early prediction will help in society a lot. It will provides the humanlife in safe way. The aim of this analysis is to develop a system that predicts the diabetes with a better accuracy. Parameters used to predict the type of Diabetes Mellitus are Glucose, Pregnancies, skin thickness, Blood pressure, Insulin, BMI, Diabetes pedigree function, age and upshot. In this we are with different machine learning algorithms, namely SVM, ANN, Decision tree, Logistic regression and Farthest first to predict the accuracy. Our experimental results show that farthest first attain superior correctness compare to dissimilar machine learning techniques.