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Resolving data interoperability in ubiquitous health profile using semi-structured storage and processing

Published: 08 April 2019 Publication History

Abstract

Advancements in the field of healthcare information management have led to the development of a plethora of software, medical devices and standards. As a consequence, the rapid growth in quantity and quality of medical data has compounded the problem of heterogeneity; thereby decreasing the effectiveness and increasing the cost of diagnostics, treatment and follow-up. However, this problem can be resolved by using a semi-structured data storage and processing engine, which can extract semantic value from a large volume of patient data, produced by a variety of data sources, at variable rates and conforming to different abstraction levels. Going beyond the traditional relational model and by re-purposing state-of-the-art tools and technologies, we present, the Ubiquitous Health Profile (UHPr), which enables a semantic solution to the data interoperability problem, in the domain of healthcare1.

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cover image ACM Conferences
SAC '19: Proceedings of the 34th ACM/SIGAPP Symposium on Applied Computing
April 2019
2682 pages
ISBN:9781450359337
DOI:10.1145/3297280
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 08 April 2019

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