MC

Current Trends in Science and Technology

an Open Access Publication ISSN: 0976-9730 | 0976-9498

Engineering and Technology

Big Data Challenges and Analytics Processing Over Medical Data

J. Tulasi Rajesh
Assistant Professor Department Information Technology S.R.K.R Engineering College, Bhimavaram, Andhra Pradesh, India
N. Deshai
Assistant Professor Department Information Technology S.R.K.R Engineering College, Bhimavaram, Andhra Pradesh, India1
Dr. G. P Saradhi Varma
Professor Department Information Technology S.R.K.R Engineering College, Bhimavaram, Andhra Pradesh, India1
Online First: February 13, 2018
| Google Scholar

Abstract

Nowadays healthcare sector grows tremendously in last few decades. Insight of how we can uncover additional value from the data generated by healthcare and government. Large amount of heterogeneous data is generated by the agencies; this includes patient’s previous medical data, laboratory test values, and current treatment given to patient, doctor’s prescription, and diagnostic reports. However, the complex distributed and highly interdisciplinary nature of medical data has underscored the limitations of traditional data analysis capabilities of data accessing, storage, processing, analyzing, distributing, and sharing.  In this paper we will discuss future trends of data mining that are used for analysis and prediction of big data. And also we review the challenges of manipulating large-scale next-generation sequencing (NGS) data and diverse clinical data derived from the EHRs for genomic medicine. Here introduce solutions for different challenges in manipulating, managing, and analyzing genomic and clinical data. Then finally data is analyzed using Apache Mahout for faster query access. These issues include Big Data benefits, its applications and opportunities in medical areas and health care. Methods and technology progress about Big Data are presented in this study.

  Submitted
Feb 13, 2018
Published
Feb 13, 2018
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References

1. A. McAfee and E. Brynjolfsson, "Big data: the management revolution," Harvard business review, pp. 60-6, 68, 128, 2012. 2. S. Sagiroglu and D. Sinanc, "Big data: A review," in Collaboration Technologies and Systems (CTS), 2013 International Conference on, 2013, pp. 42-47. 3. M. Cottle, S. Kanwal, M. Kohn, T. Strome, and N. Treister, "Transforming health care through big data. Strategies for leveraging big data in the health care industry. New York: Institute for Health Technology Transformation," 2013. 4. D. W. Bates and E. Zimlichman, "Finding patients before they crash: the next major opportunity to improve patient safety," BMJ quality & safety, pp. bmjqs-2014-003499, 2014. 5. S. Mohanty, M. Jagadeesh, and H. Srivatsa, Big Data Imperatives: Enterprise ‘Big Data’Warehouse,‘BI’Implementations and Analytics: Apress, 2013. 6. A. Rahimi, S.-T. Liaw, P. Ray, J. Taggart, and H. Yu, "Ontological specification of quality of chronic disease data in EHRs to support decision analytics: a realist review," Decision Analytics, vol. 1, pp. 1-31, 2014. 7. M. De Mul, P. Alons, P. Van der Velde, I. Konings, J. Bakker, and J. Hazelzet, "Development of a clinical data warehouse from an intensive care clinical information system," Computer methods and programs in biomedicine, vol. 105, pp. 22-30, 2012. 8. A. A. Aljumah, M. G. Ahamad, and M. K. Siddiqui, "Application of data mining: Diabetes health care in young and old patients," Journal of King Saud University-Computer and Information Sciences, vol. 25, pp. 127-136, 2013. 9. P. Groves, B. Kayyali, D. Knott, and S. Van Kuiken, "The ‘big data’revolution in healthcare," McKinsey Quarterly, 2013. 10. J.-s. Li, H.-y. Yu, and X.-g. Zhang, Data Mining in Hospital Information System: INTECH Open Access Publisher, 2011. 11. R. Steinbrook, "Personally controlled online health data-the next big thing in medical care?," New England Journal of Medicine, vol. 358, p. 1653, 2008. 12. B. Kayyali, D. Knott, and S. Van Kuiken, "The big-data revolution in US health care: Accelerating value and innovation," Mc Kinsey & Company, 2013. 13. J. Friedlin, M. Mahoui, J. Jones, and P. Jamieson, "Knowledge Discovery and Data Mining of Free Text Radiology Reports," in Healthcare Informatics, Imaging and Systems Biology (HISB), 2011 First IEEE International Conference on, 2011, pp. 89-96.
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References

1. A. McAfee and E. Brynjolfsson, "Big data: the management revolution," Harvard business review, pp. 60-6, 68, 128, 2012.
2. S. Sagiroglu and D. Sinanc, "Big data: A review," in Collaboration Technologies and Systems (CTS), 2013 International Conference on, 2013, pp. 42-47.
3. M. Cottle, S. Kanwal, M. Kohn, T. Strome, and N. Treister, "Transforming health care through big data. Strategies for leveraging big data in the health care industry. New York: Institute for Health Technology Transformation," 2013.
4. D. W. Bates and E. Zimlichman, "Finding patients before they crash: the next major opportunity to improve patient safety," BMJ quality & safety, pp. bmjqs-2014-003499, 2014.
5. S. Mohanty, M. Jagadeesh, and H. Srivatsa, Big Data Imperatives: Enterprise ‘Big Data’Warehouse,‘BI’Implementations and Analytics: Apress, 2013.
6. A. Rahimi, S.-T. Liaw, P. Ray, J. Taggart, and H. Yu, "Ontological specification of quality of chronic disease data in EHRs to support decision analytics: a realist review," Decision Analytics, vol. 1, pp. 1-31, 2014.
7. M. De Mul, P. Alons, P. Van der Velde, I. Konings, J. Bakker, and J. Hazelzet, "Development of a clinical data warehouse from an intensive care clinical information system," Computer methods and programs in biomedicine, vol. 105, pp. 22-30, 2012.
8. A. A. Aljumah, M. G. Ahamad, and M. K. Siddiqui, "Application of data mining: Diabetes health care in young and old patients," Journal of King Saud University-Computer and Information Sciences, vol. 25, pp. 127-136, 2013.
9. P. Groves, B. Kayyali, D. Knott, and S. Van Kuiken, "The ‘big data’revolution in healthcare," McKinsey Quarterly, 2013.
10. J.-s. Li, H.-y. Yu, and X.-g. Zhang, Data Mining in Hospital Information System: INTECH Open Access Publisher, 2011.
11. R. Steinbrook, "Personally controlled online health data-the next big thing in medical care?," New England Journal of Medicine, vol. 358, p. 1653, 2008.
12. B. Kayyali, D. Knott, and S. Van Kuiken, "The big-data revolution in US health care: Accelerating value and innovation," Mc Kinsey & Company, 2013.
13. J. Friedlin, M. Mahoui, J. Jones, and P. Jamieson, "Knowledge Discovery and Data Mining of Free Text Radiology Reports," in Healthcare Informatics, Imaging and Systems Biology (HISB), 2011 First IEEE International Conference on, 2011, pp. 89-96.
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