Abstract
The massive growth in data is increased day by day. This massive growth of data or high volume of data with high velocity and different variety is known as big data. Analyzing, processing and storing of this data, we require efficient techniques because the traditional techniques are not able to deal with massive growth of data. This is a research based on the big data in the health and medical field which can be used to transform the gathered data (unstructured data) into several diagnostics and predictions for personalized medicine and personalized healthcare options for identifying the accurate disease or symptoms. This will have an impact in the medical field to as it will be helpful to the doctors and authorities to take decision at the time of operation and diagnosing the patients based on the symptoms. In this paper, we develop a specialist framework through which the specialists and patients can be associated for all intents and purposes, alongside that searching for answer for storing this huge information in a progressively compelling and packed structure.
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References
Sinha A, Hripcsak G, Markatou M (2009) Large datasets in biomedicine: a discussion of salient analytic issues. J Am Med Inform Assoc 16(6):759–767
Scruggs SB (2015) Harnessing the heart of big data. Circ Res 116(7):1115–1119
Rumsfeld JS, Joynt KE, Maddox TM (2016) Big data analytics to improve cardiovascular care: promise and challenges. Nat Rev Cardiol 13(6):350–359
Slobogean GP (2015) Bigger data, bigger problems. J Orthop Trauma 29:S43–S46
Lavecchia A (2015) Machine-learning approaches in drug discovery methods and applications. Drug Discov Today 20(3):318–331
Iavindrasana J (2009) Clinical data mining: a review. Yearb Med Inform 18(01):121–133
Al Hamid HA (2017) A security model for preserving the privacy of medical big data in a healthcare cloud using a fog computing facility with pairing-based cryptography. IEEE Access 5:22313–22328
Tanaka S, Tanaka S, Kawakami K (2015) Methodological issues in observational studies and non-randomized controlled trials in oncology in the era of big data. Jpn J Clin Oncol 45(4):323–327
Binder H, Blettner M (2015) Big data in medical science—a biostatistical view: part 21 of a series on evaluation of scientific publications. Dtsch Ärztebl Int 112(9):137
Kumar S, Singh M (2019) Big data analytics for healthcare industry: impact, applications, and tools. Big Data Min Anal 2(1):48–57
Shaikh TA, Ali R (2017) A dynamic approach to medical data for smart Indian healthcare. In: 2017 international conference on big data analytics and computational intelligence (ICBDAC). IEEE
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Gandhi, Y., Singh, A., Jani, R. (2021). Big Data and Its Application in Healthcare and Medical Field. In: Kotecha, K., Piuri, V., Shah, H., Patel, R. (eds) Data Science and Intelligent Applications. Lecture Notes on Data Engineering and Communications Technologies, vol 52. Springer, Singapore. https://doi.org/10.1007/978-981-15-4474-3_18
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DOI: https://doi.org/10.1007/978-981-15-4474-3_18
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