Literature DB >> 25123717

Big Data in Science and Healthcare: A Review of Recent Literature and Perspectives. Contribution of the IMIA Social Media Working Group.

M M Hansen1, T Miron-Shatz, A Y S Lau, C Paton.   

Abstract

OBJECTIVES: As technology continues to evolve and rise in various industries, such as healthcare, science, education, and gaming, a sophisticated concept known as Big Data is surfacing. The concept of analytics aims to understand data. We set out to portray and discuss perspectives of the evolving use of Big Data in science and healthcare and, to examine some of the opportunities and challenges.
METHODS: A literature review was conducted to highlight the implications associated with the use of Big Data in scientific research and healthcare innovations, both on a large and small scale.
RESULTS: Scientists and health-care providers may learn from one another when it comes to understanding the value of Big Data and analytics. Small data, derived by patients and consumers, also requires analytics to become actionable. Connectivism provides a framework for the use of Big Data and analytics in the areas of science and healthcare. This theory assists individuals to recognize and synthesize how human connections are driving the increase in data. Despite the volume and velocity of Big Data, it is truly about technology connecting humans and assisting them to construct knowledge in new ways. Concluding Thoughts: The concept of Big Data and associated analytics are to be taken seriously when approaching the use of vast volumes of both structured and unstructured data in science and health-care. Future exploration of issues surrounding data privacy, confidentiality, and education are needed. A greater focus on data from social media, the quantified self-movement, and the application of analytics to "small data" would also be useful.

Entities:  

Keywords:  Science; analytics; big data; connectivism; healthcare; higher education; quantified self Introduction

Mesh:

Year:  2014        PMID: 25123717      PMCID: PMC4287084          DOI: 10.15265/IY-2014-0004

Source DB:  PubMed          Journal:  Yearb Med Inform        ISSN: 0943-4747


  41 in total

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Journal:  Big Data       Date:  2013-09-10       Impact factor: 2.128

6.  Choice, numeracy, and physicians-in-training performance: the case of Medicare Part D.

Authors:  Yaniv Hanoch; Talya Miron-Shatz; Helen Cole; Mary Himmelstein; Alex D Federman
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  22 in total

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Journal:  Am J Pharm Educ       Date:  2015-12-25       Impact factor: 2.047

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5.  Clinical Research Informatics for Big Data and Precision Medicine.

Authors:  C Weng; M G Kahn
Journal:  Yearb Med Inform       Date:  2016-11-10

6.  Menopause and big data: Word Adjacency Graph modeling of menopause-related ChaCha data.

Authors:  Janet S Carpenter; Doyle Groves; Chen X Chen; Julie L Otte; Wendy R Miller
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Review 7.  Big Data Technologies: New Opportunities for Diabetes Management.

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8.  Health-Enabling and Ambient Assistive Technologies: Past, Present, Future.

Authors:  R Haux; S Koch; N H Lovell; M Marschollek; N Nakashima; K-H Wolf
Journal:  Yearb Med Inform       Date:  2016-06-30

9.  Demographic and health related data of users of a mobile application to support drug adherence is associated with usage duration and intensity.

Authors:  Stefan Becker; Christopher Brandl; Sven Meister; Eckhard Nagel; Talya Miron-Shatz; Anna Mitchell; Andreas Kribben; Urs-Vito Albrecht; Alexander Mertens
Journal:  PLoS One       Date:  2015-01-28       Impact factor: 3.240

10.  Towards exergaming commons: composing the exergame ontology for publishing open game data.

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