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The Scientific World Journal has retracted this article. After conducting a thorough investigation, we have strong reason to believe that the peer review process was compromised.

This article was originally submitted to a Special Issue titled “Recent Advances in Metaheuristics and its Hybrids.” In late 2015, Dr. Xavier Delorme, the lead guest editor on the Special Issue, alerted us that his identity had been compromised. After further investigation, we discovered that several peer review reports in this issue had been submitted from similarly compromised email accounts.

We are retracting the articles in keeping with the “COPE statement on inappropriate manipulation of the peer review process.” There is no evidence that any of the authors or editors, including Dr. Delorme, were aware of this misconduct.

View the full Retraction here.


  1. C. V. Subbulakshmi and S. N. Deepa, “Medical dataset classification: a machine learning paradigm integrating particle swarm optimization with extreme learning machine classifier,” The Scientific World Journal, vol. 2015, Article ID 418060, 12 pages, 2015.
The Scientific World Journal
Volume 2015, Article ID 418060, 12 pages
Research Article

Medical Dataset Classification: A Machine Learning Paradigm Integrating Particle Swarm Optimization with Extreme Learning Machine Classifier

Department of EEE, Anna University Regional Centre, Coimbatore, Coimbatore 641 047, India

Received 19 December 2014; Accepted 2 March 2015

Academic Editor: Xavier Delorme

Copyright © 2015 C. V. Subbulakshmi and S. N. Deepa. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [11 citations]

The following is the list of published articles that have cited the current article.

  • S. Pushpalatha, and Jagdish G. Pandya, “Designing a framework for diagnosing hepatitis disease using data mining techniques,” 2017 International Conference on Algorithms, Methodology, Models and Applications in Emerging Technologies (ICAMMAET), pp. 1–6, . View at Publisher · View at Google Scholar
  • Balasaheb Tarle, and Sudarson Jena, “Improved artificial neural network for dimension reduction in medical data classification,” 2016 International Conference on Computing Communication Control and automation (ICCUBEA), pp. 1–6, . View at Publisher · View at Google Scholar
  • Faisal Abdullah Alsaby, “Golay Code classifier approach for medical diagnosis,” SoutheastCon 2016, pp. 1–6, . View at Publisher · View at Google Scholar
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  • Kannan, Kindie Biredagn Nahato, and Khanna H. Nehemiah, “Hybrid approach using fuzzy sets and extreme learning machine for classifying clinical datasets,” Informatics in Medicine Unlocked, vol. 2, pp. 1–11, 2016. View at Publisher · View at Google Scholar
  • A. Kale, and S. Sonavane, “Hybrid Feature Subset Selection Approach for Fuzzy-Extreme Learning Machine,” Data-Enabled Discovery and Applications, vol. 1, no. 1, 2017. View at Publisher · View at Google Scholar
  • Ehsan Ahmadi, Gary R. Weckman, and Dale T. Masel, “Decision making model to predict presence of coronary artery disease using neural network and C5.0 decision tree,” Journal of Ambient Intelligence and Humanized Computing, 2017. View at Publisher · View at Google Scholar
  • Elnaz Pashaei, and Nizamettin Aydin, “Binary black hole algorithm for feature selection and classification on biological data,” Applied Soft Computing, 2017. View at Publisher · View at Google Scholar
  • Nestor Rodriguez, and Sergio Rojas–Galeano, “Discovering feature relevancy and dependency by kernel-guided probabilistic model-building evolution,” BioData Mining, vol. 10, no. 1, 2017. View at Publisher · View at Google Scholar
  • Mohamed Abd El Aziz, and Aboul Ella Hassanien, “An improved social spider optimization algorithm based on rough sets for solving minimum number attribute reduction problem,” Neural Computing and Applications, 2017. View at Publisher · View at Google Scholar
  • Mohammed Eshtay, Hossam Faris, and Nadim Obeid, “Improving Extreme Learning Machine by Competitive Swarm Optimization and its application for medical diagnosis problems,” Expert Systems with Applications, 2018. View at Publisher · View at Google Scholar