Beta
ManageSearchChatDiscover
67374

Big Data Analytics for Diabetes Prediction on Apache Spark

Article

Last updated: 25 Dec 2024

OverviewSimilar Items

Subjects

-

Tags

-

Abstract

Dangerous diseases like diabetes, in which blood glucose levels are too high, some machine learning models have been used to classify or predict the patient state. Currently, the collected dataset size increases dramatically. Therefore, big data analytics technology is an essential factor in building an efficient healthcare system that can fit for the future. This paper discusses the effect of using big data analytics with different dataset sizes by usinga  different number of processing cores over apache spark. The system has been evaluated using several performance evaluation metrics like accuracy, recall, precision, time, etc. A comparative study made among various algorithms such as Support Vector Machine (SVM), Naive Bayes (NB), Decision Tree (DT), and Random Forest (RF). The experimental result shows that the most accurate models were when using RF, and SVM, and the minimum time model was when using NB algorithm.

DOI

10.21608/mjeer.2019.67374

Keywords

diabetes, Big Data Analytics, Machine Learning, Decision Tree, Random Forest, Naïve, SVM, and Apache Spark

Authors

First Name

Elhossiny

Last Name

Ibrahim

MiddleName

-

Affiliation

Department of Computer Science and Engineering Faculty of Electronic Engineering menofia-Egypt

Email

-

City

-

Orcid

-

First Name

Marwa

Last Name

Shouman

MiddleName

A.

Affiliation

Department of Computer Science and Engineering Faculty of Electronic Engineering menofia-Egypt

Email

marwa.shouman@el-eng.menofia.edu.eg

City

-

Orcid

-

First Name

Hanaa

Last Name

Torkey

MiddleName

-

Affiliation

Department of Computer Science and Engineering Faculty of Electronic Engineering menofia-Egypt

Email

htorkey@el-eng.menoufia.edu.eg

City

-

Orcid

-

First Name

Ezz El-din

Last Name

Hendan

MiddleName

-

Affiliation

Department of Computer Science and Engineering Faculty of Electronic Engineering menofia-Egypt

Email

-

City

-

Orcid

-

First Name

Ayman

Last Name

EL-SAYED

MiddleName

-

Affiliation

Department of Computer Science and Engineering Faculty of Electronic Engineering, menouf, Egypt

Email

ayman.elsayed@el-eng.menofia.edu.eg

City

Shebbin El-Kom

Orcid

0000-0002-4437-259X

Volume

28

Article Issue

ICEEM2019-Special Issue

Related Issue

9704

Issue Date

2019-12-01

Receive Date

2020-01-03

Publish Date

2019-12-07

Page Start

355

Page End

360

Print ISSN

1687-1189

Online ISSN

2682-3535

Link

https://mjeer.journals.ekb.eg/article_67374.html

Detail API

https://mjeer.journals.ekb.eg/service?article_code=67374

Order

13

Type

Original Article

Type Code

1,088

Publication Type

Journal

Publication Title

Menoufia Journal of Electronic Engineering Research

Publication Link

https://mjeer.journals.ekb.eg/

MainTitle

Big Data Analytics for Diabetes Prediction on Apache Spark

Details

Type

Article

Created At

22 Jan 2023