Efficient hybrid algorithm based on genetic with weighted fuzzy rule for developing a decision support system in prediction of heart diseases-Reference-Cited by-同舟云学术

Efficient hybrid algorithm based on genetic with weighted fuzzy rule for developing a decision support system in prediction of heart diseases

Published:2021-02-25 Issue:9 Volume:77 Page:10117-10137
ISSN:0920-8542
Container-title:The Journal of Supercomputing
language:en
Short-container-title:J Supercomput

Author:

Hameed Abdul Zubar,Ramasamy Balamurugan,Shahzad Muhammad Atif,Bakhsh Ahmed Atef S.

Funder

King Abdulaziz University

Publisher

Springer Science and Business Media LLC

Subject

Hardware and Architecture,Information Systems,Theoretical Computer Science,Software

Link

https://link.springer.com/content/pdf/10.1007/s11227-021-03677-9.pdf

Reference28 articles.

1. Dewan A, Sharma M (2015) Prediction of heart disease using a hybrid technique in data mining classification. In Computing for Sustainable Global Development, pp. 704–706

2. Toloueiashtian M, Motameni H (2018) A new clustering approach in wireless sensor networks using fuzzy system. J Supercomput 74:717–737. https://doi.org/10.1007/s11227-017-2153-0

3. Bhatla N, Jyoti K (2012) An analysis of heart disease prediction using different data mining techniques. Int J Eng 1(8):1–4

4. Vega-Rodríguez MA, Santander-Jiménez S (2019) Parallel computing in bioinformatics: a view from high-performance, heterogeneous, and cloud computing. J Supercomput 75:3369–3373. https://doi.org/10.1007/s11227-019-02934-2

5. Barretta A (2008) The functioning of co-competition in the health-care sector: an explorative analysis. Scand J Manag 24(3):209–220

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