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Using big data analytics to extract disease surveillance information from point of care diagnostic machines

Abstract:

This paper explains a novel approach for knowledge discovery from data generated by Point of Care (POC) devices. A very important element of this type of knowledge extraction is that the POC generated data would never be identifiable, thereby protecting the rights and the anonymity of the individual, whilst still allowing for vital population-level evidence to be obtained. This paper also reveals a real-world implementation of the novel approach in a big data analytics system. Using Internet ...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.pmcj.2017.06.013

Authors


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Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
Global Health Network
Role:
Author
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Institution:
University of Oxford
Division:
Medical Sciences Division
Department:
NDM
Sub department:
Experimental Medicine
Oxford college:
Green Templeton College
Role:
Author
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Institution:
University of Oxford
Division:
MSD
Department:
NDM
Sub department:
Tropical Medicine
Role:
Author
ORCID:
0000-0003-2273-5975
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Institution:
University of Oxford
Division:
Oxford Internet Institute
Oxford college:
Balliol College
Role:
Author
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Publisher:
Elsevier Publisher's website
Journal:
Pervasive and Mobile Computing Journal website
Volume:
42
Pages:
470-486
Publication date:
2017-06-27
Acceptance date:
2017-06-14
DOI:
EISSN:
1873-1589
ISSN:
1574-1192
Source identifiers:
710351
Language:
English
Keywords:
Pubs id:
pubs:710351
UUID:
uuid:67b4ef8b-b91c-4fdd-bc59-34ed3ccab7f7
Local pid:
pubs:710351
Deposit date:
2019-01-22

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