A Clustering-Based Multi-Layer Distributed Ensemble for Neurological Diagnostics in Cloud Services

IEEE Transactions on Cloud Computing

Volumn 8, Issue 2, 2020, Pages 473-483

  Chowdhury, Morshed U ^a   Abawajy, Jemal H ^a   Kelarev, Andrei ^a   Jelinek, Herbert F ^b  

^a DEAKIN UNIVERSITY   (Australia)

^b CHARLES STURT UNIVERSITY   (Australia)

Author keywords

Cardiac autonomic neuropathy; Classifiers; Cloud services; Distributed ensembles

Indexed keywords

DATA TRANSFER; HOSPITAL DATA PROCESSING; NEUROLOGY; WEB SERVICES;

BASE CLASSIFIERS; CLOUD SERVICES; DATA CENTERS;

CLASSIFICATION (OF INFORMATION);

EID: 85086758613     PISSN: None     EISSN: 21687161     Source Type: Journal    
DOI: 10.1109/TCC.2016.2567389     Document Type: Article

References (39)

1. R. Buyya, C. Vecchiola, and T. Selvi, Mastering Cloud Computing. Burlington, Massachusetts, USA: Morgan Kaufmann, 2013.
2. P. K. Tysowski and M. A. Hasan, "Hybrid attribute-and reencryption-based key management for secure and scalable mobile applications in clouds," IEEE Trans. Cloud Comput., vol. 1, no. 2, pp. 172-186, Jul. 2013.
3. K. Bilal, M. Manzano, S. U. Khan, E. Calle, K. Li, and A. Y. Zomaya, "On the characterization of the structural robustness of data center networks," IEEE Trans. Cloud Comput., vol. 1, no. 1, pp. 64-77, Jan.-Jun. 2013.
4. M. H. Ferdaus, M. Murshed, R. N. Calheiros, and R. Buyya, "Virtual machine consolidation in cloud data centers using ACO metaheuristic," in Proc. 20th Int. Conf. Parallel Process., 2014, pp. 306-317.
5. M. A. Rodriguez and R. Buyya, "Deadline based resource provisioning and scheduling algorithm for scientific workflows on clouds," IEEE Trans. Cloud Comput., vol. 2, no. 2, pp. 222-235, Apr.-Jun. 2014.
6. S. K. Garg, A. N. Toosi, S. K. Gopalaiyengar, and R. Buyya, "SLA-based virtual machine management for heterogeneous workloads in a cloud datacenter," J. Netw. Comput. Appl., vol. 45, pp. 108-120, 2014.
7. F. Martin-Sanchez, G. Lopez-Campos, and K. Gray, "Methods in biomedical informatics: A pragmatic approach," in Biomedical Informatics Methods for Personalized Medicine and Participatory Health. Amsterdam, The Netherlands: Elsevier, 2013, pp. 347-394.
8. A. J. Koutsoukis, G. H. Lopez-Campos, and F. Martin-Sanchez, "Merging personalized and participatory medicine: Interpretation of individual genomes," Studies Health Technol. Inform., vol. 202, pp. 24-27, 2014.
9. G. Lopez-Campos, R. Bellazzi, and F. Martin-Sanchez, "INDIV-3D. A new model for individual data integration and visualisation using spatial coordinates," Studies Health Technol. Inform., vol. 190, pp. 172-174, 2013.
10. J. Kilby, K. Gray, K. Elliott, J. Waycott, F. M. Sanchez, and B. Dave, "Designing a mobile augmented reality tool for the locative visualisation of biomedical knowledge," Studies Health Technol. Inform., vol. 192, pp. 652-656, 2013.
11. H. F. Jelinek, J. H. Abawajy, A. V. Kelarev, M. U. Chowdhury, and A. Stranieri, "Decision trees and multi-level ensemble classifiers for neurological diagnostics," AIMS Med. Sci., vol. 1, pp. 1-12, 2014.
12. W. Yao, J. He, G. Huang, J. Cao, and Y. Zhang, "Personalized recommendation on multi-layer context graph," in Proc. 14th Int. Conf. Web Inf. Syst. Eng., pp. 135-148, 2013.
13. J. H. Abawajy, A. V. Kelarev, and M. Chowdhury, "Multistage approach for clustering and classification of ECG data," Comput. Methods Programs Biomed., vol. 112, pp. 720-730, 2013.
14. J. He, S. Du, Z. Wang, Z. Wang, J. Zhou, and Q. Lou, "Linearlypolarized short-pulse AOM Q-switched 978 nm photonic crystal fiber laser," Opt. Express, vol. 21, pp. 29 240-29 245, 2013.
15. W. Yao, J. He, G. Huang, J. Cao, and Y. Zhang, "A graph-based model for context-aware recommendation using implicit feedback data," World Wide Web, vol. 18, pp. 1351-1371, 2015.
16. A. Stranieri, J. Abawajy, A. Kelarev, S. Huda, M. Chowdhury, and H. F. Jelinek, "An approach for Ewing test selection to support the clinical assessment of cardiac autonomic neuropathy," Artif. Intell. Med., vol. 58, pp. 185-193, 2013.
17. L. Wang, J. C. Bezdek, C. Leckie, and R. Kotagiri, "Selective sampling for approximate clustering of very large data sets," Int. J. Intell. Syst., vol. 23, pp. 313-331, 2008.
18. L. Wang, C. Leckie, R. Kotagiri, and J. Bezdek, "Approximate pairwise clustering for large data sets via sampling plus extension," Pattern Recog., vol. 44, pp. 222-235, 2011.
19. F. Li, J. He, G. Huang, Y. Zhang, and Y. Shi, "A clustering-based link prediction method in social networks," Procedia Comput. Sci., vol. 29, pp. 432-442, 2014.
20. P. B. Perez Villamil, A. Romera Lopez, S. Hernandez Prieto, G. Lopez Campos, A. Calles, J. A. Lopez Asenjo, J. Sanz Ortega, C. Fernandez Perez, J. Sastre, R. Alfonso, T. Caldes, F. Martin Sanchez, and E. Diaz Rubio, "Colon cancer molecular subtypes identified by expression profiling and associated to stroma, mucinous type and different clinical behavior," BMC Cancer, vol. 12, pp. 1-16, Art. no. 260, 2012.
21. X. Yin, B.-H. Ng, J. He, Y. Zhang, and D. Abbott, "Accurate image analysis of the retina using Hessian matrix and binarisation of thresholded entropy with application of texture mapping," PLoS ONE, vol. 9, pp. 1-17, Art. no. e95 943, 2014.
22. J. Chan, N. X. Vinh, W. Liu, J. Bailey, C. A. Leckie, R. Kotagiri, and J. Pei, "Structure-aware distance measures for comparing clusterings in graphs," in Proc. Asia-Pacific Conf. Adv. Knowl. Discovery Data Mining, 2014, vol. 8443, pp. 362-373.
23. G. Huang, J. He, Y. Zhang, W. Zhou, H. Liu, P. Zhang, Z. Ding, Y. You, and J. Cao, "Mining streams of short text for analysis of world-wide event evolutions," World Wide Web, vol. 18, pp. 1201-1217, 2015.
24. R. Hassan, M. Hossain, J. Bailey, G. Macintyre, J. W. K. Ho, and R. Kotagiri, "A voting approach to identify a small number of highly predictive genes using multiple classifiers," BMC Bioinform., vol. 10, pp. 1-12, Art. no. S19, 2009.
25. R. Islam, W. Zhou, and M. U. Chowdhury, "Email categorization using (2+1)-tier classification algorithms," in Proc. 7th IEEE/ACIS Int. Conf. Comput. Inf. Sci., In conjunction 2nd IEEE/ACIS Int. Workshop e-Activity, 2008, pp. 276-281.
26. K. K. Gupta, B. Nath, and R. Kotagiri, "Layered approach using conditional random fields for intrusion detection," IEEE Trans. Dependable Secure Comput., vol. 7, no. 1, pp. 35-49, Jan.-Mar. 2010.
27. A. Goder and V. Filkov, "Consensus clustering algorithms: comparison and refinement," in Proc. 10th SIAM Workshop Algorithm Eng. Exp., Jan. 19, 2008, pp. 109-117.
28. M. Hall, E. Frank, G. Holmes, B. Pfahringer, P. Reutemann, and I. H. Witten, "The WEKA data mining software: an update," SIGKDD Explorations, vol. 11, pp. 10-18, 2009.
29. I. H. Witten, E. Frank, and M. A. Hall, Data Mining: Practical Machine Learning Tools and Techniques, 3rd ed., Amsterdam, The Netherlands: Elsevier, 2011.
30. R. R. Bouckaert, E. Frank, M. Hall, R. Kirkby, P. Reutemann, A. Seewald, and D. Scuse, "WEKA manual for version 3-7-12," [Online]. Available: http://www.cs.waikato.ac.nz/ml/weka/, viewed 15 January, 2015.
31. A. Fahad, N. Alshatri, Z. Tari, A. Alamri, I. Khalil, A. Zomaya, S. Foufou, and A. Bouras, "A survey of clustering algorithms for big data: Taxonomy & empirical analysis," IEEE Trans. Emerging Topics Comput., vol. 2, no. 3, pp. 267-279, Sept. 2014.
32. D. Cornforth and H. F. Jelinek, "Automated classification reveals morphological factors associated with dementia," Appl. Soft Comput., vol. 8, pp. 182-190, 2007.
33. D. J. Ewing, J. W. Campbell, and B. F. Clarke, "The natural history of diabetic autonomic neuropathy," Q. J. Med., vol. 49, pp. 95-100, 1980.
34. D. J. Ewing, C. N. Martyn, R. J. Young, and B. F. Clarke, "The value of cardiovascular autonomic function tests: 10 years experience in diabetes," Diabetes Care, vol. 8, pp. 491-498, 1985.
35. A. H. Khandoker, H. F. Jelinek, and M. Palaniswami, "Identifying diabetic patients with cardiac autonomic neuropathy by heart rate complexity analysis," BioMed. Eng. OnLine, vol. 8, pp. 1-12, 2009.
36. D. J. Ewing and B. F. Clarke, "Diagnosis and management of diabetic autonomic neuropathy," Brit. Med. J., vol. 285, pp. 916-918, 1982.
37. M. Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems, 3rd ed., New York, NY, USA: Addison-Wesley, 2011.
38. L. I. Kuncheva, Combining Pattern Classifiers: Methods and Algorithms. New York, NY, USA: Wiley, 2004.
39. H. K. Ho, M. J. Kuiper, and R. Kotagiri, "PConPy-a Python module for generating 2D protein maps," Bioinformatics, vol. 24, pp. 2934-2935, 2008.