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The Scientific World Journal
Volume 2014, Article ID 859279, 10 pages
Research Article

Cloud Based Metalearning System for Predictive Modeling of Biomedical Data

Faculty of Organizational Sciences, University of Belgrade, Jove Ilića 154, 11000 Belgrade, Serbia

Received 20 December 2013; Accepted 21 January 2014; Published 14 April 2014

Academic Editors: R. Colomo-Palacios and V. Stantchev

Copyright © 2014 Milan Vukićević et al. 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 [9 citations]

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

  • Selvaraj Rani Bhavani, Jagatheesan Senthilkumar, Arul Gnanaprakasam Chilambuchelvan, Dhanabalachandran Manjula, Ramasamy Krishnamoorthy, and Arputharaj Kannan, “CIMIDx: Prototype for a Cloud-Based System to Support Intelligent Medical Image Diagnosis With Efficiency,” JMIR Medical Informatics, vol. 3, no. 1, pp. e12, 2015. View at Publisher · View at Google Scholar
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  • Hend Ibrahim Shousha, Abubakr Hussein Awad, Dalia Abdelhamid Omran, Mayada Mohamed Elnegouly, and Mahasen Mabrouk, “Data mining machine learning algorithms using IL28B genotype and biochemical markers best predicted advanced liver fibrosis in chronic HCV,” Japanese Journal of Infectious Diseases, 2017. View at Publisher · View at Google Scholar
  • Vivek Navale, and Philip E. Bourne, “Cloud computing applications for biomedical science: A perspective,” PLOS Computational Biology, vol. 14, no. 6, pp. e1006144, 2018. View at Publisher · View at Google Scholar
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  • Hana Alharthi, “Healthcare predictive analytics: An overview with a focus on Saudi Arabia,” Journal of Infection and Public Health, vol. 11, no. 6, pp. 749–756, 2018. View at Publisher · View at Google Scholar
  • Chadsuthi, Kesorn, Siriyasatien, and Jampachaisri, “Dengue epidemics prediction: A survey of the state-of-the-art based on data science processes,” IEEE Access, vol. 6, pp. 53757–53795, 2018. View at Publisher · View at Google Scholar