• Register
  • Login

European Journal of Molecular & Clinical Medicine

  1. Home
  2. Analyzing Diabetic Data Using Naive-Bayes Classifier

Current Issue

By Issue

By Author

By Subject

Author Index

Keyword Index

About Journal

Aims and Scope

Editorial Board

Publication Ethics

Indexing and Abstracting

Related Links

FAQ

Peer Review Process

Journal Metrics

News

Analyzing Diabetic Data Using Naive-Bayes Classifier

    Authors

    • A. Sharmila Agnal
    • E. Saraswathi

    Assistant Professor, Department of Computer Science and Engineering, SRM Institute of Science and Technology, Chennai, India

,

Document Type : Research Article

  • Article Information
  • Download
  • Export Citation
  • Statistics
  • Share

Abstract

Approximately 422 million people across the world have diabetes, particularly in countries where the average income is in the middle and lower end of the economic spectrum. Statistics reveal that every year, about 1.6 million deaths are recorded which can be directly attributed to diabetes. The graph suggests that number of cases as well as the prevalence of diabetes have been steadily incrementing over the past few decades. Through this new implementation of the Bayesian Classifier, raw medical data is analyzed and the risk of diabetes diagnosis based on each patient’s medical information can be calculated. The raw data is converted into class labels and the likelihood of a positive potential diabetes case is derived, as a probability (≤1). This can not only be used by healthcare professionals but also by common users, and can be useful in detecting the risk and preventing it in time without taking any medical tests. This classifier uses very basic information that would be known to each patient or can easily be obtained.

Keywords

  • Diabetes
  • Naive-Bayes Classifier
  • prediction
  • healthcare
  • Decision Tree
  • Confusion Matrix
  • XML
  • PDF 370.03 K
  • RIS
  • EndNote
  • Mendeley
  • BibTeX
  • APA
  • MLA
  • HARVARD
  • VANCOUVER
    • Article View: 283
    • PDF Download: 2,476
European Journal of Molecular & Clinical Medicine
Volume 7, Issue 4
November 2020
Page 2687-2699
Files
  • XML
  • PDF 370.03 K
Share
Export Citation
  • RIS
  • EndNote
  • Mendeley
  • BibTeX
  • APA
  • MLA
  • HARVARD
  • VANCOUVER
Statistics
  • Article View: 283
  • PDF Download: 2,476

APA

Agnal, A. S., & Saraswathi, E. (2020). Analyzing Diabetic Data Using Naive-Bayes Classifier. European Journal of Molecular & Clinical Medicine, 7(4), 2687-2699.

MLA

A. Sharmila Agnal; E. Saraswathi. "Analyzing Diabetic Data Using Naive-Bayes Classifier". European Journal of Molecular & Clinical Medicine, 7, 4, 2020, 2687-2699.

HARVARD

Agnal, A. S., Saraswathi, E. (2020). 'Analyzing Diabetic Data Using Naive-Bayes Classifier', European Journal of Molecular & Clinical Medicine, 7(4), pp. 2687-2699.

VANCOUVER

Agnal, A. S., Saraswathi, E. Analyzing Diabetic Data Using Naive-Bayes Classifier. European Journal of Molecular & Clinical Medicine, 2020; 7(4): 2687-2699.

  • Home
  • About Journal
  • Editorial Board
  • Submit Manuscript
  • Contact Us
  • Glossary
  • Sitemap

News

 

For Special Issue Proposal : editor.ejmcm21@gmail.com

Newsletter Subscription

Subscribe to the journal newsletter and receive the latest news and updates

© Journal Management System. Powered by ejournalplus