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An Efficient Agent Based Data Management Method of NoSQL Environments for Health Care Applications
Background: As medical knowledge is continuously expanding and diversely located, Health Information Technology (HIT) applications are proposed as a good prospect for improving not only the efficiency and the effectiveness but also the quality of healthcare services delivery. The technologies expect...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8000069/ https://www.ncbi.nlm.nih.gov/pubmed/33805721 http://dx.doi.org/10.3390/healthcare9030322 |
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author | Kotsilieris, Theodore |
author_facet | Kotsilieris, Theodore |
author_sort | Kotsilieris, Theodore |
collection | PubMed |
description | Background: As medical knowledge is continuously expanding and diversely located, Health Information Technology (HIT) applications are proposed as a good prospect for improving not only the efficiency and the effectiveness but also the quality of healthcare services delivery. The technologies expected to shape such innovative HIT architectures include: Mobile agents (Mas) and NoSQL technologies. Mobile agents provide an inherent way of tackling distributed problems of accessing heterogeneous and spatially diverse data sources. NoSQL technology gains ground for the development of scalable applications with non-static and open data schema from complex and diverse sources. Methods and Design: This paper conducts a twofold study: It attempts a literature review of the applications based on the mobile agent (MA) and NoSQL technologies for healthcare support services. Subsequently, a pilot system evaluates the NoSQL technology against the relational one within a distributed environment based on mobile agents for information retrieval. Its objective is to study the feasibility of developing systems that will employ ontological data representation and task implementation through mobile agents towards flexible and transparent health data monitoring. Results and Discussion: The articles studied focus on applying mobile agents for patient support and healthcare services provision thus as to make a positive contribution to the treatment of chronic diseases. In addition, attention is put on the design of platform neutral techniques for clinical data gathering and dissemination over NoSQL. The experimental environment was based on the Apache Jena Fuseki NoSQL server and the JAVA Agent DEvelopment Framework -JADE agent platform. The results reveal that the NoSQL implementation outperforms the standard relational one. |
format | Online Article Text |
id | pubmed-8000069 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-80000692021-03-28 An Efficient Agent Based Data Management Method of NoSQL Environments for Health Care Applications Kotsilieris, Theodore Healthcare (Basel) Article Background: As medical knowledge is continuously expanding and diversely located, Health Information Technology (HIT) applications are proposed as a good prospect for improving not only the efficiency and the effectiveness but also the quality of healthcare services delivery. The technologies expected to shape such innovative HIT architectures include: Mobile agents (Mas) and NoSQL technologies. Mobile agents provide an inherent way of tackling distributed problems of accessing heterogeneous and spatially diverse data sources. NoSQL technology gains ground for the development of scalable applications with non-static and open data schema from complex and diverse sources. Methods and Design: This paper conducts a twofold study: It attempts a literature review of the applications based on the mobile agent (MA) and NoSQL technologies for healthcare support services. Subsequently, a pilot system evaluates the NoSQL technology against the relational one within a distributed environment based on mobile agents for information retrieval. Its objective is to study the feasibility of developing systems that will employ ontological data representation and task implementation through mobile agents towards flexible and transparent health data monitoring. Results and Discussion: The articles studied focus on applying mobile agents for patient support and healthcare services provision thus as to make a positive contribution to the treatment of chronic diseases. In addition, attention is put on the design of platform neutral techniques for clinical data gathering and dissemination over NoSQL. The experimental environment was based on the Apache Jena Fuseki NoSQL server and the JAVA Agent DEvelopment Framework -JADE agent platform. The results reveal that the NoSQL implementation outperforms the standard relational one. MDPI 2021-03-13 /pmc/articles/PMC8000069/ /pubmed/33805721 http://dx.doi.org/10.3390/healthcare9030322 Text en © 2021 by the author. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ). |
spellingShingle | Article Kotsilieris, Theodore An Efficient Agent Based Data Management Method of NoSQL Environments for Health Care Applications |
title | An Efficient Agent Based Data Management Method of NoSQL Environments for Health Care Applications |
title_full | An Efficient Agent Based Data Management Method of NoSQL Environments for Health Care Applications |
title_fullStr | An Efficient Agent Based Data Management Method of NoSQL Environments for Health Care Applications |
title_full_unstemmed | An Efficient Agent Based Data Management Method of NoSQL Environments for Health Care Applications |
title_short | An Efficient Agent Based Data Management Method of NoSQL Environments for Health Care Applications |
title_sort | efficient agent based data management method of nosql environments for health care applications |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8000069/ https://www.ncbi.nlm.nih.gov/pubmed/33805721 http://dx.doi.org/10.3390/healthcare9030322 |
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