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Proceedings ArticleDOI

Big data for better health planning

TLDR
The thought of data in healthcare and the results of various surveys to show the impact of big data are introduced and the tools and techniques comprising Hadoop, Storm, Spark and HPCC - big data solution offered to solve big data issues and challenges are presented.
Abstract
The exponential evolution of data in health care has brought a lot of challenges in terms of data transfer, storage, computation and analysis For healthcare usage and applications, ample patient information and historical data, which enclose rich and significant insights that can be exposed using advanced tools and techniques as well as latest machine learning algorithms Though, the size and rapidity of such great dimensional data requires new big data analytics framework This paper introduces the thought of data in healthcare and the results of various surveys to show the impact of big data Few case studies of big data analytics in healthcare is presented Last section is about the tools and techniques comprising Hadoop, Storm, Spark and HPCC - big data solution offered to solve big data issues and challenges

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Citations
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Journal ArticleDOI

Big data analytics for healthcare industry: impact, applications, and tools

TL;DR: The conceptual architecture of big data analytics for healthcare which involves the data gathering history of different branches, the genome database, electronic health records, text/imagery, and clinical decisions support system is explored.
Journal ArticleDOI

Analytics, challenges and applications in big data environment: a survey

TL;DR: Big data refer to the massive amounts and varieties of information in the structured and unstructured form, generated by social networking sites, biomedical equipment, financial companies, internet...
Journal ArticleDOI

A Systematic Review of Techniques and Sources of Big Data in the Healthcare Sector

TL;DR: The sources and techniques of Big Data used in the health sector represent a relevant factor in terms of effectiveness, since it allows the application of predictive analysis techniques in tasks such as: identification of patients at risk of reentry or prevention of hospital or chronic diseases infections, obtaining predictive models of quality.
Journal ArticleDOI

Chronic Diseases and Health Monitoring Big Data: A Survey

TL;DR: This review investigates recent research efforts and conducts a comprehensive overview of the work on medical big data, especially as related to chronic diseases and health monitoring, and attempts to combine common big data technologies with special medical needs by analyzing in detail existing works of medicalbig data.
References
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Proceedings ArticleDOI

Big data: A review

TL;DR: This paper presents an overview of big data's content, scope, samples, methods, advantages and challenges, and discusses privacy concern on it.
Proceedings ArticleDOI

Big data: Issues, challenges, tools and Good practices

TL;DR: The various challenges and issues in adapting and accepting Big data technology, its tools (Hadoop) are discussed in detail along with the problems Hadoop is facing.
Proceedings ArticleDOI

Big Data Processing in Cloud Computing Environments

TL;DR: This paper presents the key issues of big data processing, including cloud computing platform, cloud architecture, cloud database and data storage scheme, and introduces Map Reduce optimization strategies and applications reported in the literature.
Journal ArticleDOI

Big data security

Colin Tankard
- 01 Jul 2012 - 
TL;DR: Controls need to be placed around the data itself, rather than the applications and systems that store the data, to ensure it's secure in the process, says Colin Tankard of Digital Pathways.
Proceedings ArticleDOI

Inside "Big Data management": ogres, onions, or parfaits?

TL;DR: The history of systems for managing "Big data" as well as today's activities and architectures are reviewed from the (perhaps biased) perspective of three "database guys" who have been watching this space for a number of years and are currently working together on "Big Data" problems.
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