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A Comparative Study Of Artificial Intelligence Techniques For Categorization And Prediction Of Heart Diseases

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Last updated: 26 Dec 2024

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Abstract

Heart failure (HF) is one of the most common diseases in recent years, and a large number of people die annually around the world from it. The heart is considered one of the most important organs in the human body, so it requires high accuracy when predicting the presence of heart disease or not, as an error in prediction may cause human death, so it requires a high-accuracy method in predicting HF. Artificial intelligence (AI) plays a large and important role in many fields today, especially in the medical field, as AI helps doctors obtain a quick and accurate diagnosis of the patient's condition, which contributes to saving time during the diagnosis. It is important to predict HF using AI to help with rapid and accurate diagnosis and thus reduce the number of deaths from this disease. AI techniques increase the accuracy of predicting whether or not HF is present compared to traditional methods. Also, in rural areas where there are fewer physicians, it is very important to provide such technologies to aid in diagnosis. Many studies point to new AI-based HF prediction techniques. These technologies relied on different algorithms and datasets of different sizes and types. Each of these technologies has advantages and limitations. Therefore, this paper presents an illustrative study of the most advanced AI methods for HF prediction. This study also included a comparison between the different methods based on the most famous standards.  

DOI

10.21608/fcihib.2023.211465.1087

Keywords

artificial intelligence, Machine Learning, Deep learning, Feature Extraction, Feature Selection, Heart failure prediction

Authors

First Name

عبدالله

Last Name

رضا رشوان

MiddleName

-

Affiliation

كلية الحاسبات و المعلومات جامعة كفرالشيخ,كفر الشيخ,مصر

Email

abdullahrashwan16@gmail.com

City

Alexandria

Orcid

0000-0002-8531-5647

First Name

ليلى

Last Name

الفنجري

MiddleName

-

Affiliation

قسم نظم المعلومات, كلية الحاسبات والذكاء الاصطناعى ,جامعة حلوان, مصر

Email

lailaelfangary@gmail.com

City

-

Orcid

-

First Name

صفاء

Last Name

عزام

MiddleName

-

Affiliation

قسم نظم المعلومات,کلية الحاسبات والذکاء الاصطناعي, جامعة حلوان,مصر

Email

eng_safaa_azam@yahoo.com

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-

Orcid

-

Volume

6

Article Issue

1

Related Issue

45796

Issue Date

2024-01-01

Receive Date

2023-05-16

Publish Date

2024-01-01

Page Start

11

Page End

21

Print ISSN

2537-0901

Online ISSN

2535-1397

Article File

FCIHIB_Volume 6_Issue 1_Pages 11-21.pdf

PDF . 824.4kB

Link

https://fcihib.journals.ekb.eg/article_338479.html

Detail API

https://fcihib.journals.ekb.eg/service?article_code=338479

Order

338,479

Type

المقالة الأصلية

Type Code

1,411

Publication Type

Journal

Publication Title

النشرة المعلوماتية في الحاسبات والمعلومات

Publication Link

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

MainTitle

A Comparative Study Of Artificial Intelligence Techniques For Categorization And Prediction Of Heart Diseases

Details

Type

Article

Created At

26 Dec 2024