Big Data Analytics in Health Care

  • Tahmeena FatimaEmail author
  • Singaraju Jyothi
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1054)


In today’s world, data is growing exponentially and widespread accessibility of data led to analyze and visualize data effectively using analytical techniques in healthcare industry. Big data analytics play a vital role and provides long-term benefits in tremendously handling huge explosive data. In this paper, we present an overview of different big data platform tools and different technologies that support big data analytics in health care. It also describes different steps involved in big data analytics process and also presents ways to improve health care by considering various facts by using big data analytics. As big data analytics has the potential to provide useful insight in health care, this article uses a review methodology to categorize the uses of big data in health care. This study provides a baseline to assess the essential prospects of computational health informatics and the use of big data in health care in understanding different scopes of big data platforms.


Big data Healthcare Big data analytics Review of big data platforms and tools 


  1. 1.
    Improved Approaches to Handle Bigdata through Hadoop KLEF University, IndiaGoogle Scholar
  2. 2.
    Y. Demchenko, Z. Zhao, P. Grosso, A. Wibisono, C. de Laat: Addressing big data challenges for scientific data infrastructure. In: IEEE 4th International Conference on Cloud Computing Technology and Science (CloudCom 2012). IEEE Computing Society, based in California, USA, Taipei, Taiwan, pp. 614–617 (2012)Google Scholar
  3. 3.
    Al-Jarrah, O.Y., Yoo, P.D., Muhaidat, S., Karagiannidis, G.K., Taha, K.: Efficient machine learning for big data: a review. Data Res. 2, 87–93 (2015). Scholar
  4. 4.
    Chen, H., Fuller, S.S., Friedman, C., Hersh, W.: Medical Informatics: Knowledge Management and Data Mining in Biomedicine, 8. Springer Science & Business Media (2006)Google Scholar
  5. 5.
    Ritu, C., Jangade, R.: A robust model for big healthcare data analytics. Cloud System and Big Data Engineering (Confluence), 2016 6th International Conference. IEEE, New York (2016)Google Scholar
  6. 6.
    Sadilek, A., Kautz, H., Silenzio, V.: Modeling spread of disease from social interactions. In: Sixth AAAI International Conference on Weblogs and Social Media (ICWSM) (2012).
  7. 7.
    Erl, T., Khattak, W., Buhler, P.: Big Data Fundamentals: Concepts, Drivers & Techniques. Prentice Hall. Part of the The Prentice Hall Service Technology Series from Thomas Erl Series (2016 Jan 5)Google Scholar
  8. 8.
    Agrawal, D., et. al.: Challenges and Opportunities with Big Data. Big Data White Paper-Computing Research Association (2012 Feb). Available
  9. 9.
    Hashem, I.A.T., Yaqoob, I., Badrul Anuar, N., Mokhtar, S., Gani, A., Ullah Khan, S.: The rise of “Big Data” on cloud computing: review and open research issues. Inf. Syst. 47, 98–115 (2014). Scholar
  10. 10.
    Archenaa, J., Mary Anita, E.A.: A survey of big data analytics in healthcare and government. Procedia Comput. Sci. 50, 408–413 (2015). Big Data, Cloud and Computing Challenges. Available:
  11. 11.
    Wicks, P., Massagli, M., Frost, J., Brownstein, C., Okun, S., Vaughan, T., et al.: Sharing health data for better outcomes on PatientsLikeMe. J. Med. Internet Res. 12, e19 (2010). Scholar
  12. 12.
    U.S. Government, Department of Health and Human Services, Federal Register, Rules and Regulations, 74(2009)56123-56131. Available from:
  13. 13.
    Sai Jyothi, B., Jyothi, S.: Doc-based modelling for medical big data. IADS SSRN:, Volume No. 01, Issue No. 03.[Scopus] (2018)
  14. 14.
    Russom, P.: Big data analytics; TDWI best practices report; Fourth Quarter; Report No.: 9.14.2011; TDWI: Renton, WV, USA (2011)Google Scholar
  15. 15.
    Mohammed, E.A., Far, B.H., Naugler, C.: Applications of the MapReduce programming framework to clinical big data analysis: current landscape and future trends. BioData Min. 7, 22 (2014)CrossRefGoogle Scholar
  16. 16.
    The R project for statistical computing.
  17. 17.
    Patel, J.A., Sharma, P.: Big data for better health planning. In: IEEE International Conference on Advances in Engineering & Technology Research, August 2014Google Scholar
  18. 18.
  19. 19.
    Hows, D., Membrey, P., Plugge, E., Hawkins, T.: Introduction to mongodb. In: The Definitive Guide to MongoDB, 16, p. 1. Springer, Berkeley, CA (2015)Google Scholar
  20. 20.
  21. 21.
    Gowsalya, M., Krushitha, K., Valliyammai, C.: Predicting the risk of readmission of diabetic patients using MapRe-duce. 2014 Sixth International Conference on Advanced Computing (ICoAC). IEEE, New York (2014)Google Scholar
  22. 22.
    Gomathi, S., Narayani, V.: Implementing big data analytics to predict systemic lupus erythematosus. In: 2015 International Conference on Innovations in In-formation, Embedded and Communication Systems (ICIIECS). IEEE, New York (2015)Google Scholar
  23. 23.
    Sheriff, C.I., Naqishbandi, T., Geetha, A.: Healthcare informatics and analytics framework. 2015 International Conference on Computer Communication and Informatics (ICCCI). IEEE, New York (2015)Google Scholar
  24. 24.
    Prasad, S.T., et al.: Diabetic data analysis in big data with predictive method. 2017 International Conference on Algorithms, Methodology, Models and Applications in Emerging Technologies (ICAMMAET). IEEE, New York (2017)Google Scholar
  25. 25.
    Ojha, M., Mathur, K.: Proposed application of big data analytics in healthcare at Maharaja Yeshwantrao Hospital. 2016 3rd MEC International Conference on Big Data and Smart City (ICBDSC). IEEE, New York (2016)Google Scholar
  26. 26.
    Kalyankar, G.D., Poojara, S.R., Dharwadkar, N.V.: Predictive analysis of diabetic patient data using machine learning and Hadoop. In: 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC). IEEE, New York (2017)Google Scholar
  27. 27.
    Chennamsetty, H., Chalasani, S., Riley, D.: Predictive analytics on Electronic Health Records (EHRs) using Hadoop and Hive. 2015 IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT). IEEE, New York (2015)Google Scholar
  28. 28.
    Asri, H., et al.: Big data in healthcare: challenges and opportunities. 2015 International Conference on Cloud Technologies and Applications (CloudTech). IEEE, New York (2015)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Wadi Addawasir, RiyadhSaudi Arabia
  2. 2.Department of Computer Science, SPMVVTirupatiIndia

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