• #0 (no title)
  • #0 (no title)
  • About
  • Facebook
  • Twitter
  • RSS
(As ISO 9001:2015 Certified Publications)
    • Quick Search
    • Advanced Search
  • Home
  • Editorial Policy
  • Author Guidelines
  • Submission
  • Copyright Form
  • Career
  • Contact us
  • Subscription

Back to Journal

Home»Articles»Data Mining for the Prediction of Heart Disease: A Literature Survey

JournalCover

Asian Journal of Computer Science and Technology (AJCST)

Editor Dr. K. Ganesh
Print ISSN : 2249-0701
Frequency : Quarterly

Data Mining for the Prediction of Heart Disease: A Literature Survey

Author : P. Umasankar and V. Thiagarasu
Volume 8 No.1 January-March 2019 pp 1-6

Abstract

The health care environment is found to be rich in information, but poor in extracting knowledge from the information. This is because of the lack of effective analysis tool to discover hidden relationships and trends in them. By applying the data mining techniques, valuable knowledge can be extracted from the health care system. Heart disease is a group of condition affecting the structure and functions of heart and has many root causes. Heart disease is the leading cause of death in the world over past ten years. Researches have been made with many hybrid techniques for diagnosing heart disease. This paper deals with an overall review of application of data mining in heart disease prediction.

Keywords

Cardio Vascular Disease, Data Mining, Feature Selection, Classification, Association Rule Mining, Clustering

Full Text:

References

[1] Nahar, Jesmin, et al., “Association rule mining to detect factors which contribute to heart disease in males and females”, Expert Systems with Applications, Vol. 40, No. 4, pp. 1086-1093, 2013.
[2] Vijiyarani, S., and S. Sudha, “An efficient classification tree technique for heart disease prediction”, International Conference on Research Trends in Computer Technologies (ICRTCT-2013) Proceedings published in International Journal of Computer Applications (IJCA)(0975–8887). Vol. 201, 2013.
[3] Gayathri, P., and N. Jaisankar, “Comprehensive study of heart disease diagnosis using data mining and soft computing techniques”, 2013.
[4] Shouman, Mai, Tim Turner, and Rob Stocker, “Integrating clustering with different data mining techniques in the diagnosis of heart disease”, J. Comput. Sci. Eng, Vol. 20, No. 1, 2013.
[5] Amato, Filippo, et al., “Artificial neural networks in medical diagnosis”, pp. 47-58, 2013.
[6] Persi Pamela, I., and P. Gayathri, “A fuzzy optimization technique for the prediction of coronary heart disease using decision tree”, 2013.
[7] Chaurasia, Vikas, and Saurabh Pal, “Data mining approach to detect heart diseases”, 2014.
[8] K. Thenmozhi, and P. Deepika, “Heart disease prediction using classification with different decision tree techniques”, International Journal of Engineering Research and General Science, Vol. 2, No. 6, pp. 6-11, 2014.
[9] Kim, Jae-Kwon, et al., “Adaptive mining prediction model for content recommendation to coronary heart disease patients”, Cluster computing, Vol. 17, No. 3, pp. 881-891, 2014.
[10] Seera, Manjeevan, and CheePeng Lim, “A hybrid intelligent system for medical data classification”, Expert Systems with Applications, Vol. 41, No. 5, pp. 2239-2249, 2014.
[11] Bashir, Saba, UsmanQamar, and M. YounusJaved, “An ensemble-based decision support framework for intelligent heart disease diagnosis”, Information Society (i-Society), 2014 International Conference on. IEEE, 2014.
[12] Shabana, ASMI P., and S. Justin Samuel, “An analysis and accuracy prediction of heart disease with association rule and other data mining techniques”, Journal of Theoretical and Applied Information Technology, Vol. 79, No. 2, pp. 254-60, 2015.
[13] A. J. Aljaaf, et al., “Predicting the likelihood of heart failure with a multi-level risk assessment using decision tree”, Technological Advances in Electrical, Electronics and Computer Engineering (TAEECE), 2015 Third International Conference on IEEE, 2015.
[14] Bashir, Saba, UsmanQamar, and Farhan Hassan Khan, “BagMOOV: A novel ensemble for heart disease prediction bootstrap aggregation with multi-objective optimized voting”, Australasian physical & engineering sciences in medicine, Vol. 38, No. 2, pp. 305-323, 2015.
[15] Kim, Jaekwon, Jongsik Lee, and Youngho Lee, “Data-mining-based coronary heart disease risk prediction model using fuzzy logic and decision tree”, Healthcare informatics research, Vol. 21, No. 3, pp. 167-174, 2015.
[16] Joshi, Sujata, and Mydhili K. Nair, “Prediction of heart disease using classification-based data mining techniques”, Computational Intelligence in Data Mining-. Springer, New Delhi, Vol. 2, pp.503-511, 2015.
[17] Chadha, Ritika, et al.,, “Application of data mining techniques on heart disease prediction: a survey”, Emerging Research in Computing, Information, Communication and Applications. Springer, New Delhi, pp. 413-426, 2016.
[18] Choi, Edward, et al.,, “Using recurrent neural network models for early detection of heart failure onset”, Journal of the American Medical Informatics Association, Vol. 24, No. 2, pp. 361-370, 2016.
[19] Saxena, Kanak, and Richa Sharma, “Efficient Heart Disease Prediction System”,Procedia Computer Science, Vol. 85, pp. 962-969, 2016.
[20] Goldstein, A. Benjamin Ann Marie Navar, and Rickey E. Carter, “Moving beyond regression techniques in cardiovascular risk prediction: applying machine learning to address analytic challenges”, European heart journal, Vol. 38, No. 23, pp. 1805-1814, 2016.
[21] Miranda, Eka, et al., “Detection of cardiovascular disease risk’s level for adults using naive Bayes classifier”, Healthcare informatics research, Vol. 22, No. 3, pp. 196-205, 2016.
[22] Chadha, Ritika, and ShubhankarMayank, “Prediction of heart disease using data mining techniques”, CSI transactions on ICT, Vol. 4.2-4, pp. 193-198, 2016.
[23] Singh, Garima, et al., “Heart disease prediction using Naïve Bayes”, International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395-0056, 2017.
[24] Pouriyeh, Seyedamin, et al., “A comprehensive investigation and comparison of Machine Learning Techniques in the domain of heart disease”, Computers and Communications (ISCC), IEEE Symposium on IEEE, 2017.
[25] Samuel, Oluwarotimi Williams, et al., “An integrated decision support system based on ANN and Fuzzy_AHP for heart failure risk prediction”, Expert Systems with Applications, Vol. 68, pp. 163-172, 2017.
[26] Tripoliti, E. Evanthia et al., “Heart failure: diagnosis, severity estimation and prediction of adverse events through machine learning techniques”, Computational and structural biotechnology journal, Vol. 15, pp. 26-47, 2017.
[27] Acharya, U. Rajendra, et al., “Application of empirical mode decomposition (EMD) for automated identification of congestive heart failure using heart rate signals”, Neural Computing and Applications, Vol. 28, No. 10, pp. 3073-3094, 2017.
[28] Seah, C. Y. Jarrel, et al., “Chest radiographs in congestive heart failure: visualizing neural network learning”,Radiology (2018): 180887, 2018.
[29] Kumar, PriyanMalarvizhi, and Usha Devi Gandhi, “A novel three-tier Internet of Things architecture with machine learning algorithm for early detection of heart diseases”,Computers & Electrical Engineering , Vol. 65, pp. 222-235, 2018.
[30] Jain, Divya, and Vijendra Singh, “Feature selection and classification systems for chronic disease prediction: A review”,Egyptian Informatics Journal, 2018.
[31] Paul, Animesh Kumar, et al., “Adaptive weighted fuzzy rule-based system for the risk level assessment of heart disease”, Applied Intelligence, Vol. 48, No. 7, pp. 1739-1756, 2018.
[32] Manogaran, Gunasekaran, R. Varatharajan, and M. K. Priyan, “Hybrid recommendation system for heart disease diagnosis based on multiple kernel learning with adaptive neuro-fuzzy inference system”, Multimedia tools and applications, Vol. 77, No. 4, pp. 4379-4399, 2018.

Asian Journal of Computer Science and Technology is a peer-reviewed international journal that publishes high-quality scientific articles (both theory and practice) and research papers covering all aspects of future computer and Information Technology areas. Topics include, but are not limited to:

Foundations of High-performance ComputingTheory of algorithms and computability

Parallel & distributed computing

Computer networks

Neural networks

LAN/WAN/MAN

Database theory & practice

Mobile Computing for e-Commerce

Future Internet architecture

Protocols and services

Mobile and ubiquitous networks

Green networking

Internet content search

Opportunistic networking

Network applications

Network scaling and limits

Artifial Intelligences

Pattern/Image Recognitions

Communication Network

Information Security

Knowledge Management

Management Information systems

Multimedia communicatiions

Operations research

Optical networks

Software Engineering

Virtual reality

Web Technologies

Wireless technology

The health care environment is found to be rich in information, but poor in extracting knowledge from the information. This is because of the lack of effective analysis tool to discover hidden relationships and trends in them. By applying the data mining techniques, valuable knowledge can be extracted from the health care system. Heart disease is a group of condition affecting the structure and functions of heart and has many root causes. Heart disease is the leading cause of death in the world over past ten years. Researches have been made with many hybrid techniques for diagnosing heart disease. This paper deals with an overall review of application of data mining in heart disease prediction.

Editor-in-Chief
Dr. K. Ganesh
Global Lead, Supply Chain Management, Center of Competence and Senior Knowledge
Expert at McKinsey and Company, India
[email protected]
Editorial Advisory Board
Dr. Eng. Hamid Ali Abed AL-Asadi
Department of Computer Science, Basra University, Iraq
[email protected]
Dr. Norjihan Binti Abdul Ghani
Department of Information System, University of Malaya, Malaysia
[email protected]
Dr. Christos Bouras
Department of Computer Engineering & Informatics, University of Patras, Greece
[email protected]
Dr. Maizatul Akmar Binti Ismail
Department of Information System, University of Malaya, Malaysia
[email protected]
Dr. Harold Castro
Department of Systems Engineering and Computing, University of the Andes, Colombia
[email protected]
Dr. Busyairah Binti Syd Ali
Department of Software Engineering, University of Malaya, Malaysia
[email protected]
Dr. Sri Devi Ravana
Department of Information system, University of Malaya, Malaysia
[email protected]
Dr. Karpaga Selvi Subramanian
Department of Computer Engineering, Mekelle University, Ethiopia
[email protected]
Dr. Mazliza Binti Othman
Department of Computer System & Technology, University of Malaya, Malaysia
[email protected]
Dr. Chiam Yin Kia
Department of Software Engineering, University of Malaya, Malaysia
[email protected]
Dr. OUH Eng Lieh
Department of Information Systems, Singapore Management University, Singapore
[email protected]

2016

2015

2014

  • Results
  • Asian Review of Mechanical Engineering (ARME)
  • career

2013

  • Home
  • Shop
  • My Account
  • Logout
  • Contact us
  • The Asian Review of Civil Engineering (TARCE)

2012

  • Asian Journal of Electrical Sciences(AJES)
  • Asian Journal of Computer Science and Technology (AJCST)
  • Asian Journal of Information Science and Technology (AJIST)
  • Asian Journal of Engineering and Applied Technology (AJEAT)
  • Asian Journal of Science and Applied Technology (AJSAT)
  • Asian Journal of Managerial Science (AJMS)
  • Asian Review of Social Sciences (ARSS)

2011

2010

    Table of Contents

    Editorial Note

    Editorial Dr. K. Ganesh

    Editor-in-Chief
    Dr. K. Ganesh
    Global Lead, Supply Chain Management, Center of Competence and Senior Knowledge
    Expert at McKinsey and Company, India
    [email protected]
    Editorial Advisory Board
    Dr. Eng. Hamid Ali Abed AL-Asadi
    Department of Computer Science, Basra University, Iraq
    [email protected]
    Dr. Norjihan Binti Abdul Ghani
    Department of Information System, University of Malaya, Malaysia
    [email protected]
    Dr. Christos Bouras
    Department of Computer Engineering & Informatics, University of Patras, Greece
    [email protected]
    Dr. Maizatul Akmar Binti Ismail
    Department of Information System, University of Malaya, Malaysia
    [email protected]
    Dr. Harold Castro
    Department of Systems Engineering and Computing, University of the Andes, Colombia
    [email protected]
    Dr. Busyairah Binti Syd Ali
    Department of Software Engineering, University of Malaya, Malaysia
    [email protected]
    Dr. Sri Devi Ravana
    Department of Information system, University of Malaya, Malaysia
    [email protected]
    Dr. Karpaga Selvi Subramanian
    Department of Computer Engineering, Mekelle University, Ethiopia
    [email protected]
    Dr. Mazliza Binti Othman
    Department of Computer System & Technology, University of Malaya, Malaysia
    [email protected]
    Dr. Chiam Yin Kia
    Department of Software Engineering, University of Malaya, Malaysia
    [email protected]
    Dr. OUH Eng Lieh
    Department of Information Systems, Singapore Management University, Singapore
    [email protected]

    Articles

Advanced Search

You can submit your research paper to the journal in just a few clicks. Please follow the steps outlined below: 1. Register your details and select to be an Author 2. Log in with your user name and password 3. ‘Start a new submission’ and follow these 5 steps:

[gravityform id="1" name="Registration" title="false" description="false"]

Privacy Statement

The names and email addresses entered in this journal site will be used exclusively for the stated purposes of this journal and will not be made available for any other purpose or to any other party.

Privacy Statement

The names and email addresses entered in this journal site will be used exclusively for the stated purposes of this journal and will not be made available for any other purpose or to any other party.

Lorem1 ipsum dolor sit amet, consectetur adipiscing elit. Nulla convallis ultricies scelerisque. Fusce dolor augue, sollicitudin eget lacus vitae, rutrum commodo lacus. Praesent ullamcorper facilisis dui. Sed suscipit id lorem ut dapibus. Integer dictum cursus nisl, quis ullamcorper augue. Sed non rutrum mauris. Maecenas in dolor est. Donec eget sagittis mi. Sed non leo eu odio mollis pulvinar vitae et leo. Integer eu feugiat tortor. Duis massa purus, eleifend id erat eget, hendrerit semper risus. Suspendisse cursus varius dapibus

Lorem1 ipsum dolor sit amet, consectetur adipiscing elit. Nulla convallis ultricies scelerisque. Fusce dolor augue, sollicitudin eget lacus vitae, rutrum commodo lacus. Praesent ullamcorper facilisis dui. Sed suscipit id lorem ut dapibus. Integer dictum cursus nisl, quis ullamcorper augue.

Subscription

Subscription (for 12 issues):
Rs. 5000; Overseas - USD 500;
Cheque drawn in favour of "Informatics Publishing Limited"
Click here to download online subscription form

Download

DD Mailing Address

Lorem1 ipsum dolor sit amet,
Lorem1 ipsum dolor sit amet,
Lorem1 ipsum dolor sit amet.

BACK TO TOP

Outstanding Scholars

The Journals honor Outstanding Scholars in various fields. Scholar of the Month should have contributed to their field and to the larger community. Recipients will be nominated by the Advisory Board and approved by the Editor-in-Chief of the allied journals published by The Research Publication. Scholar of the Month will be displayed in the web portal of the concerned journal.

Please send your brief write up to [email protected]

Editors and Reviewers

The Research Publication is seeking qualified researchers to join its editorial team as Associate Editor, Editorial Advisory Board Member, and Reviewers.
Kindly send your details to [email protected]

Call For Papers

Authors are requested to submit their papers electronically to [email protected] with mentioning the journal title.

Mailing Address

The Research Publication 1/611, Maruthi Nagar, Rakkipalayam Post, Coimbatore – 641 031, Tamil Nadu, India Phone No.: 0422 2461001

  • About
  • Editorial Policy
  • Author Guidelines
  • Contact us
  • Copyright
  • Facebook
  • Twitter
  • RSS

© 2015 The Research Publication. All rights reserved.

The Research Publication
  • Home
  • Editorial Policy
  • Author Guidelines
  • Submission
  • Copyright Form
  • Career
  • Contact us
  • Subscription