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Big Data Analytics in Medicine and Healthcare
This paper surveys big data with highlighting the big data analytics in medicine and healthcare. Big data characteristics: value, volume, velocity, variety, veracity and variability are described. Big data analytics in medicine and healthcare covers integration and analysis of large amount of comple...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
De Gruyter
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6340124/ https://www.ncbi.nlm.nih.gov/pubmed/29746254 http://dx.doi.org/10.1515/jib-2017-0030 |
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author | Ristevski, Blagoj Chen, Ming |
author_facet | Ristevski, Blagoj Chen, Ming |
author_sort | Ristevski, Blagoj |
collection | PubMed |
description | This paper surveys big data with highlighting the big data analytics in medicine and healthcare. Big data characteristics: value, volume, velocity, variety, veracity and variability are described. Big data analytics in medicine and healthcare covers integration and analysis of large amount of complex heterogeneous data such as various – omics data (genomics, epigenomics, transcriptomics, proteomics, metabolomics, interactomics, pharmacogenomics, diseasomics), biomedical data and electronic health records data. We underline the challenging issues about big data privacy and security. Regarding big data characteristics, some directions of using suitable and promising open-source distributed data processing software platform are given. |
format | Online Article Text |
id | pubmed-6340124 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | De Gruyter |
record_format | MEDLINE/PubMed |
spelling | pubmed-63401242019-01-28 Big Data Analytics in Medicine and Healthcare Ristevski, Blagoj Chen, Ming J Integr Bioinform Review Article This paper surveys big data with highlighting the big data analytics in medicine and healthcare. Big data characteristics: value, volume, velocity, variety, veracity and variability are described. Big data analytics in medicine and healthcare covers integration and analysis of large amount of complex heterogeneous data such as various – omics data (genomics, epigenomics, transcriptomics, proteomics, metabolomics, interactomics, pharmacogenomics, diseasomics), biomedical data and electronic health records data. We underline the challenging issues about big data privacy and security. Regarding big data characteristics, some directions of using suitable and promising open-source distributed data processing software platform are given. De Gruyter 2018-05-10 /pmc/articles/PMC6340124/ /pubmed/29746254 http://dx.doi.org/10.1515/jib-2017-0030 Text en ©2018, Blagoj Ristevski and Ming Chen, published by De Gruyter, Berlin/Boston http://creativecommons.org/licenses/by-nc-nd/4.0 This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. |
spellingShingle | Review Article Ristevski, Blagoj Chen, Ming Big Data Analytics in Medicine and Healthcare |
title | Big Data Analytics in Medicine and Healthcare |
title_full | Big Data Analytics in Medicine and Healthcare |
title_fullStr | Big Data Analytics in Medicine and Healthcare |
title_full_unstemmed | Big Data Analytics in Medicine and Healthcare |
title_short | Big Data Analytics in Medicine and Healthcare |
title_sort | big data analytics in medicine and healthcare |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6340124/ https://www.ncbi.nlm.nih.gov/pubmed/29746254 http://dx.doi.org/10.1515/jib-2017-0030 |
work_keys_str_mv | AT ristevskiblagoj bigdataanalyticsinmedicineandhealthcare AT chenming bigdataanalyticsinmedicineandhealthcare |