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Titlebook: Big Data in Healthcare; Extracting Knowledge Pouria Amirian,Trudie Lang,Francois van Loggerenbe Book 2017 The Editors and Authors 2017 heal

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發(fā)表于 2025-3-21 16:18:26 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Big Data in Healthcare
期刊簡稱Extracting Knowledge
影響因子2023Pouria Amirian,Trudie Lang,Francois van Loggerenbe
視頻videohttp://file.papertrans.cn/186/185705/185705.mp4
發(fā)行地址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
學科分類SpringerBriefs in Pharmaceutical Science & Drug Development
圖書封面Titlebook: Big Data in Healthcare; Extracting Knowledge Pouria Amirian,Trudie Lang,Francois van Loggerenbe Book 2017 The Editors and Authors 2017 heal
影響因子.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..
Pindex Book 2017
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Book 2017d 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..
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Electrical Properties of Glass, workflow procedures and so on. This broad availability of data has led to increasing interest in methods for extracting useful information and knowledge from data and data-driven decision making. Data Science is the science and art of using computational methods to identify and discover influential patterns in data.
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