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A Novel Approach to Predict Diabetes Mellitus by Statistical Analysis and using Advanced Classification Algorithm

by Saima Sultana, Mahmudul Hasan Khandaker, Abdullah Al Momen, Mohoshi Haque, Nazmus Sakib
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 175 - Number 38
Year of Publication: 2020
Authors: Saima Sultana, Mahmudul Hasan Khandaker, Abdullah Al Momen, Mohoshi Haque, Nazmus Sakib
10.5120/ijca2020920950

Saima Sultana, Mahmudul Hasan Khandaker, Abdullah Al Momen, Mohoshi Haque, Nazmus Sakib . A Novel Approach to Predict Diabetes Mellitus by Statistical Analysis and using Advanced Classification Algorithm. International Journal of Computer Applications. 175, 38 ( Dec 2020), 17-24. DOI=10.5120/ijca2020920950

@article{ 10.5120/ijca2020920950,
author = { Saima Sultana, Mahmudul Hasan Khandaker, Abdullah Al Momen, Mohoshi Haque, Nazmus Sakib },
title = { A Novel Approach to Predict Diabetes Mellitus by Statistical Analysis and using Advanced Classification Algorithm },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2020 },
volume = { 175 },
number = { 38 },
month = { Dec },
year = { 2020 },
issn = { 0975-8887 },
pages = { 17-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume175/number38/31700-2020920950/ },
doi = { 10.5120/ijca2020920950 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:40:36.905672+05:30
%A Saima Sultana
%A Mahmudul Hasan Khandaker
%A Abdullah Al Momen
%A Mohoshi Haque
%A Nazmus Sakib
%T A Novel Approach to Predict Diabetes Mellitus by Statistical Analysis and using Advanced Classification Algorithm
%J International Journal of Computer Applications
%@ 0975-8887
%V 175
%N 38
%P 17-24
%D 2020
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Diabetes is a severe, enduring disorder with a huge impact on the existence and health of individuals and the people around them. It happens due to insufficient production of insulin in human body. After a thorough research on this disease, it can be said that diagnosing diabetes at the early stage can help patients to control it and also knowing the probability of having the disease can be useful to the patients for taking necessary steps. So, for the prediction of this disease, a different approach has been taken which is developing a mathematical equation. To develop this equation, some basic medical information of a person have been used as parameters. Using this equation, 80% accuracy has been achieved. Three machine learning algorithms have been used: Logistic Regression, Support Vector Machine (SVM) and K-Nearest Neighbor (KNN) on the dataset to verify the credibility of this equation. The accuracy attained for Logistic Regression, SVM and KNN is 86%, 91% and 83% respectively.

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Index Terms

Computer Science
Information Sciences

Keywords

Diabetes Mellitus Logistic Regression SVM KNN Machine Learning Algorithms Prediction System Age Body Mass Index (BMI) Blood Pressure Blood Sugar Exercise Time and Sleeping Time.

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