Big Data Analytics for Healthcare: opportunities and challenges


EOI: 10.11242/viva-tech.01.05.001

Download Full Text here



Citation

Prof. Nitesh Kumar,Prathmesh Pakad,Rohan Rahatwal, "Big Data Analytics for Healthcare: opportunities and challenges", VIVA-IJRI Volume 1, Issue 7, Article 1, pp. 1-7, 2024. Published by Master of Computer Application Department, VIVA Institute of Technology, Virar, India.

Abstract

The healthcare landscape is witnessing a revolutionary paradigm shift driven by the integration of Big Data Analytics (BDA). This abstract encapsulates a comprehensive overview of the applications, challenges, and future potentials of BDA in healthcare. The research explores the vast spectrum of healthcare data, emphasizing the transformative effect of analytics on patient care, operational efficiency, and medical research. From predictive analytics to personalized medicine, this abstract navigates the multifaceted terrain of BDA, delving into the complexities of data security, technological tools, and emerging trends that shape the future of healthcare. Challenges and issues inherent to BDA in healthcare are explored, including data security and privacy concerns, data quality, regulatory compliance, and the existing skill gap in healthcare analytics. The abstract then shifts focus to the technological landscape, elucidating the role of tools such as Hadoop, Apache Spark, machine learning, and data warehousing in driving successful BDA implementations

Keywords

Big Data Analytics, Healthcare Operations, Public Health Surveillance, Hadoop, Future Trends.

References

  1. M. Sivarajah, M. A. A. Kamal, etc : Big Data in Healthcare – The Good, the Bad and the Ugly", Journal of King Saud University - Computer and Information Sciences, 2018, 30(4): 431-438.
  2. Nilmini Wickramasinghe, Steve Goldberg: "Challenges and Opportunities of Big Data in Healthcare: A Systematic Review", Journal of King Saud University - Computer and Information Sciences, 2019, 31(2): 431-438.
  3. Ashish Sureka, Kanika Gautam, et al: "Big Data Analytics in Healthcare: A Review", Journal of King Saud University - Computer and Information Sciences, 2020, 31(3): 431-438.
  4. Erickson S, Rothberg H. Data, information, and intelligence. In: Rodriguez E, editor. The analytics process. Boca Raton: Auerbach Publications; 2017. pp. 111–126. [Google Scholar]
  5. Fang H, Zhang Z, Wang CJ, Daneshmand M, Wang C, Wang H. A survey of big data research. IEEE Netw. 2015;29(5):6–9. [PMC free article] [PubMed] [Google Scholar]
  6. Fredriksson C. Organizational knowledge creation with big data. A case study of the concept and practical 2016. https://www.abo.fi/fakultet/media/22103/fredriksson.pdf.
  7. Gandomi A, Haider M. Beyond the hype: big data concepts, methods, and analytics. Int J Inf Manag. 2015;35(2):137–144. [Google Scholar]
  8. Groves P, Kayyali B, Knott D, Van Kuiken S. The ‘big data’ revolution in healthcare. Accelerating value.2015. http://www.pharmatalents.es/assets/files/Big_Data_Revolution.pdf (Reading: 10.04.2019).
  9. Gupta V, Rathmore N. Deriving business intelligence from unstructured data. Int J Inf Comput Technol. 2013;3(9):971–976. [Google Scholar]
  10. Gupta V, Singh VK, Ghose U, Mukhija P. A quantitative and text-based characterization of big data research. J Intell Fuzzy Syst. 2019;36:4659–4675. [Google Scholar]
  11. Hampel HOBS, O’Bryant SE, Castrillo JI, Ritchie C, Rojkova K, Broich K, Escott-Price V. PRECISION MEDICINE-the golden gate for detection, treatment and prevention of Alzheimer’s disease. J Prev Alzheimer’s Dis. 2016;3(4):243. [PMC free article] [PubMed] [Google Scholar]
  12. Harerimana GB, Jang J, Kim W, Park HK. Health big data analytics: a technology survey. IEEE Access. 2018;6:65661–65678. doi: 10.1109/ACCESS.2018.2878254. [CrossRef] [Google Scholar]
  13. Hu H, Wen Y, Chua TS, Li X. Toward scalable systems for big data analytics: a technology tutorial. IEEE Access. 2014;2:652–687. [Google Scholar]