Big Data in Healthcare: Extracting Knowledge from Point-of-Care Machines [Paperback]

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.

Introduction  Improving Healthcare with Big Data.- Data Science and Analytics.- Big Data and Big Data Technologies.- Big Data Analytics for Extracting Disease Surveillance Information: An Untapped Opportunity.- Ebola and Twitter. What Insights Can Public Health Draw from Social Media?

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)

Pouria Amirian has a PhD in Geospatial Information Science (GIS) and is a Principal Research Scientist in Data Science and Big Data at the Ordnance Survey GB and a Data Science Research Associate with the Global Health Network. He managed and led a joint project (Oxford and Stanford) on Using Big Data Analysis Tools to Extract Disease Surveillance Information from Point-of-Care Diagnostic Machines. Pouria has done research and development projects and lectured about Big Data, Data Scienlƒ]