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DC Field | Value | Language |
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dc.contributor.author | Pruet Boonma | en_US |
dc.contributor.author | Juggapong Natwichai | en_US |
dc.contributor.author | Krit Khwanngern | en_US |
dc.contributor.author | Panutda Nantawad | en_US |
dc.date.accessioned | 2020-04-02T15:02:43Z | - |
dc.date.available | 2020-04-02T15:02:43Z | - |
dc.date.issued | 2019-01-01 | en_US |
dc.identifier.issn | 23674520 | en_US |
dc.identifier.issn | 23674512 | en_US |
dc.identifier.other | 2-s2.0-85078479188 | en_US |
dc.identifier.other | 10.1007/978-3-030-02607-3_45 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85078479188&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/67749 | - |
dc.description.abstract | © Springer Nature Switzerland AG 2019. Generally speaking, healthcare service providers, such as hospitals, maintains a large collection of data. In the last decade, healthcare industry becomes aware that data analytics is a crucial tool to help providing a better services. However, there are several obstacles to prevent a successful deployment of such systems, among them are data quality and system performance. To address the issues, this paper proposes a distributed data-as-a-service framework that help to assure level of data quality and also improve the performance of data analytics. Preliminary evaluation suggests that the proposed system is scale well to large amount of user requests. | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Engineering | en_US |
dc.title | Dahs: a distributed data-as-a-service framework for data analytics in healthcare | en_US |
dc.type | Book Series | en_US |
article.title.sourcetitle | Lecture Notes on Data Engineering and Communications Technologies | en_US |
article.volume | 24 | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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