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107526

Building a respiratory diseases recognition system Using Data mining techniques

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Last updated: 04 Jan 2025

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Abstract

Respiratory diseases are among the most common causes of morbidity and mortality worldwide. Computer-assisted learning tools have been shown to promote self-directed learning and enhance problem-solving and predicting skills. However, few have been developed in the area of respiratory medicine. Thus, we aimed in this study to build a framework to predict the respiratory system diseases by applying Data Mining Techniques (DMT) on clinical information. The framework composed of three main phases which are preprocessing phase, data mining phase and evaluation phase to evaluate the built prediction model. This Approach statistics shows acceptable results.

DOI

10.21608/fcihib.2020.107526

Keywords

Data Mining Techniques, Decision Tree, prediction model, respiratory

Authors

First Name

Ahmed

Last Name

Saleh Abdu

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Orcid

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First Name

Mostafa-Sami

Last Name

M. Mostafa

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Orcid

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First Name

Aya

Last Name

Sedky Adly

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Volume

2

Article Issue

1

Related Issue

16267

Issue Date

2020-01-01

Receive Date

2020-01-31

Publish Date

2020-01-01

Page Start

10

Page End

16

Print ISSN

2537-0901

Online ISSN

2535-1397

Article File

FCIHIB_Volume 2_Issue 1_Pages 10-16.pdf

PDF . 855.3kB

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https://fcihib.journals.ekb.eg/article_107526.html

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https://fcihib.journals.ekb.eg/service?article_code=107526

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المقالة الأصلية

Type Code

1,411

Publication Type

Journal

Publication Title

النشرة المعلوماتية في الحاسبات والمعلومات

Publication Link

https://fcihib.journals.ekb.eg/

MainTitle

Building a respiratory diseases recognition system Using Data mining techniques

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Article

Created At

23 Jan 2023