Big Data in Healthcare
Extracting Knowledge from Point-of-Care Machines
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Beschreibung
This book reviews a number of issues including: Why data generated from POC machines are considered as Big Data. What are the challenges in storing, managing, extracting knowledge from data from POC devices? Why is it inefficient to use traditional data analysis with big data?
What are the solutions for the mentioned issues and challenges? What type of analytics skills are required in health care? What big data technologies and tools can be used efficiently with data generated from POC devices? This book shows how it is feasible to store vast numbers of anonymous data and ask highly specific questions that can be performed in real-time to give precise and meaningful evidence to guide public health policy.
Asks the central question why data generated from POC machines are considered Big Data Demonstrates the feasibilty of storing vast amounts of anonymous data Asks highly specific questions in real-time Provides precise and meaningful evidence to guide public policy Includes supplementary material: sn.pub/extras
Autor*in
Pouria Amirian
Themen in »Big Data in Healthcare«
health care data analytics POC devices biosensors cloud storage improving healthcare data science data analytics big data technologies disease survellience public health and social media
Stimmen zu »Big Data in Healthcare«
“This book serves as an introduction to and definition of what constitutes ‘big data’ and touches on some of the issues encountered in using large data sets, including analytical and ethical challenges. … The book seems most appropriate for pharmaceutical company managers and executives, as it creates an awareness of the availability and potential of tapping into big data.” (Michael R. Jacobs, Doody's Book Reviews, January, 2018)
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