scholarly journals Big Data Analytics in Healthcare

Today, data is constantly increasing and it becomes very hard to handled data skilfully in the usual way. It is also quite expensive, unproductive and very hard to manage data. That's the reason why the super-important technologies are entering in the work place. In the medical field data is increasing day by day and it becomes very hard to manage, analysis and store data in paper pen work. Recent, big data technology, plays major role in the management, organization and analysis of data. Big data technology has been applied towards improving patient profile of care delivery. Biomedical image, generating each day in huge number can be analyzed better with big data technology along with machine learning and artificial intelligence.Research rate in this field has the potential to provide meaningful result in identification of diseases. Change in DNA can predict many future chronic disease. Research also demanded useful, updated, and accurate data. . It becomes possible for public to identify their health risk by their own.

2015 ◽  
Vol 2015 ◽  
pp. 1-16 ◽  
Author(s):  
Ashwin Belle ◽  
Raghuram Thiagarajan ◽  
S. M. Reza Soroushmehr ◽  
Fatemeh Navidi ◽  
Daniel A. Beard ◽  
...  

The rapidly expanding field of big data analytics has started to play a pivotal role in the evolution of healthcare practices and research. It has provided tools to accumulate, manage, analyze, and assimilate large volumes of disparate, structured, and unstructured data produced by current healthcare systems. Big data analytics has been recently applied towards aiding the process of care delivery and disease exploration. However, the adoption rate and research development in this space is still hindered by some fundamental problems inherent within the big data paradigm. In this paper, we discuss some of these major challenges with a focus on three upcoming and promising areas of medical research: image, signal, and genomics based analytics. Recent research which targets utilization of large volumes of medical data while combining multimodal data from disparate sources is discussed. Potential areas of research within this field which have the ability to provide meaningful impact on healthcare delivery are also examined.


Author(s):  
Shweta Kumari

n a business enterprise there is an enormous amount of data generated or processed daily through different data points. It is increasing day by day. It is tough to handle it through traditional applications like excel or any other tools. So, big data analytics and environment may be helpful in the current scenario and the situation discussed above. This paper discussed the big data management ways with the impact of computational methodologies. It also covers the applicability domains and areas. It explores the computational methods applicability scenario and their conceptual design based on the previous literature. Machine learning, artificial intelligence and data mining techniques have been discussed for the same environment based on the related study.


2019 ◽  
Vol 8 (3) ◽  
pp. 27-31
Author(s):  
R. P. L. Durgabai ◽  
P. Bhargavi ◽  
S. Jyothi

Data, in today’s world, is essential. The Big Data technology is rising to examine the data to make fast insight and strategic decisions. Big data refers to the facility to assemble and examine the vast amounts of data that is being generated by different departments working directly or indirectly involved in agriculture. Due to lack of resources the pest analysis of rice crop is in poor condition which effects the production. In Andhra Pradesh rice is cultivated in almost all the districts. The goal is to provide better solutions for finding pest attack conditions in all districts using Big Data Analytics and to make better decisions on high productivity of rice crop in Andhra Pradesh.


2018 ◽  
Vol 7 (4.5) ◽  
pp. 485
Author(s):  
Samson Fadiya ◽  
Arif Sari

The adoption of Web 2.0 technologies, Internet of Things, etc. by individuals and organization has led to an explosion of data. As it stands, existing Relational Database Management Systems (RDBMSs) are incapable of handling this deluge of data. The term Big Data was coined to represent these vast, fast and complex datasets that regular RDBMSs could not handle. Special tools or frameworks were developed to deal with processing, managing and storing this big data. These tools are capable of functioning in distributed industry- standard environments thereby maintaining efficiency and effectiveness at a business level. Apache Hadoop is an example of such a framework. This report discusses big data, it origins, opportunities and challenges that it presents, big data analytics and the application of big data using existing big data tools or frameworks. It also discusses Apache Hadoop as a big data framework and provides a basic overview of this technology from technological and business perspectives.  


2021 ◽  
Vol 8 (2) ◽  
pp. 60-63
Author(s):  
Xin Wang ◽  
Lizhang Xu ◽  
Bin Liu ◽  
Fangxiang Zhang

This article explores the roles and responsibilities of government, hospital and medical workers in the construction of precision medical system under the background of big data, which provide reference advices for setting out big data-related policies by the government, promoting the applications of big data technology in the medical field by the hospital, and using big data technology to help improve the efficiency of clinical diagnosis and treatment or make precise medical practice by medical workers. The main research contents are followed. It presents some problems and countermeasures in setting out big data-related policies by the government. This article studies the work tips of hospitals, as the main body of the implementation of the responsibility and obligation, and how to use big data technology in application. Meanwhile, it tries to analyze the problems and difficulties which hospitals and medical workers need to pay attention to applying big data technology in precision medicine.


2021 ◽  
Author(s):  
Kiran Chaudhary ◽  
Mansaf Alam ◽  
Mabrook S. Al-Rakhami ◽  
Abdu Gumaei

Abstract Almost many consumers are inclined by social media to purchase the product and spend more money on purchasing. We got the data from social media to analyse the consumer behaviour. We have considered the consumer data from Facebook, Twitter, LinkedIn and YouTube. There is diversity and high-speed, high volume data is coming from social media, so we used big data technology. Big Data Technology is the recent technology is used in various field of research. In this paper we have used the concept of big data technology to process data and analyse to predict the consumer behaviour on social media. We have analysed the consumer behaviour based on certain parameter and criteria. we have analysed the consumer perception, attitude towards the social media. For doing the prediction we have pre-process the data to make the quality data so that we can take the quality decision based on outcome of our model. We have used the predictive big data analytics technique to analyse the consumer behaviour prediction in this paper.


Author(s):  
Balasree K ◽  
Dharmarajan K

In rapid development of Big Data technology over the recent years, this paper discussing about the Machine Learning (ML) playing role that is based on methods and algorithms to Big Data Processing and Big Data Analytics. In evolutionary fields and computing fields of developments that both are complementing each other. Big Data: The rapid growth of such data solutions needed to be studied and provided to handle then to gain the knowledge from datasets and extracting values due to the data sets are very high in velocity and variety. The Big data analytics are involving and indicating the appropriate data storage and computational outline that enhanced by using Scalable Machine Learning Algorithms and Big Data Analytics then the analytics to reveal the massive amounts of hidden data’s and secret correlations. This type of Analytic information useful for organizations and companies to gain deeper knowledge, development and getting advantages over the competition. When using this Analytics we can predict the accurate implementation over the data. This paper presented about the detailed review of state-of-the-art developments and overview of advantages and challenges in Machine Learning Algorithms over big data analytics.


Author(s):  
Janet Chan

Internet and telecommunications, ubiquitous sensing devices, and advances in data storage and analytic capacities have heralded the age of Big Data, where the volume, velocity, and variety of data not only promise new opportunities for the harvesting of information, but also threaten to overload existing resources for making sense of this information. The use of Big Data technology for criminal justice and crime control is a relatively new development. Big Data technology has overlapped with criminology in two main areas: (a) Big Data is used as a type of data in criminological research, and (b) Big Data analytics is employed as a predictive tool to guide criminal justice decisions and strategies. Much of the debate about Big Data in criminology is concerned with legitimacy, including privacy, accountability, transparency, and fairness. Big Data is often made accessible through data visualization. Big Data visualization is a performance that simultaneously masks the power of commercial and governmental surveillance and renders information political. The production of visuality operates in an economy of attention. In crime control enterprises, future uncertainties can be masked by affective triggers that create an atmosphere of risk and suspicion. There have also been efforts to mobilize data to expose harms and injustices and garner support for resistance. While Big Data and visuality can perform affective modulation in the race for attention, the impact of data visualization is not always predictable. By removing the visibility of real people or events and by aestheticizing representations of tragedies, data visualization may achieve further distancing and deadening of conscience in situations where graphic photographic images might at least garner initial emotional impact.


Author(s):  
Pushpa Mannava

Big Data is a data evaluation method makes it possible for by recent breakthroughs in details and interactions modern technology. However, big data evaluation requires a massive quantity of calculating resources making fostering costs of big data technology is not inexpensive for lots of small to tool business. In this paper, we detail the benefits as well as obstacles associated with deploying big data analytics through cloud computing. We suggest that cloud computer can support the storage space as well as computing requirements of big data analytics. This paper provides a detailed overview of cloud computing and deployment of big data analytics in the cloud.


Author(s):  
RAJIB BISWAS

— Big Data analytics has come a long way since its inception. This field is growing day by day. With the advent of large handling capacity of computational analysis of modern computing systems as well as Internet of Things (IoT), this field has revolutionized the way we think about data. It has influenced the major domains such as healthcare, automobile, computing, climatology, and space communications. Of late, the health care sector has been largely influenced by this. This communication deals with the areas of healthcare where big data analytics has been largely influential. Encompassing the basics of Big Data Analytics (BDA) driven by IoT, the applications of it in healthcare sector are outlined, accompanied by future expectations. Additionally, it also presents a comprehensive analysis of recent application with special reference to Covid-19 in this sector.


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