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Clinical Decision Support Systems for Comorbidity: Architecture, Algorithms, and Applications

In this paper, we present the design of a clinical decision support system (CDSS) for monitoring comorbid conditions. Specifically, we address the architecture of a CDSS by characterizing it from three layers and discuss the algorithms in each layer. Also we address the applications of CDSSs in a fe...

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Detalles Bibliográficos
Autores principales: Fan, Aihua, Lin, Di, Tang, Yu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5361053/
https://www.ncbi.nlm.nih.gov/pubmed/28373881
http://dx.doi.org/10.1155/2017/1562919
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author Fan, Aihua
Lin, Di
Tang, Yu
author_facet Fan, Aihua
Lin, Di
Tang, Yu
author_sort Fan, Aihua
collection PubMed
description In this paper, we present the design of a clinical decision support system (CDSS) for monitoring comorbid conditions. Specifically, we address the architecture of a CDSS by characterizing it from three layers and discuss the algorithms in each layer. Also we address the applications of CDSSs in a few real scenarios and analyze the accuracy of a CDSS in consideration of the potential conflicts when using multiple clinical practice guidelines concurrently. Finally, we compare the system performance in our design with that in the other design schemes. Our study shows that our proposed design can achieve a clinical decision in a shorter time than the other designs, while ensuring a high level of system accuracy.
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spelling pubmed-53610532017-04-03 Clinical Decision Support Systems for Comorbidity: Architecture, Algorithms, and Applications Fan, Aihua Lin, Di Tang, Yu Int J Telemed Appl Research Article In this paper, we present the design of a clinical decision support system (CDSS) for monitoring comorbid conditions. Specifically, we address the architecture of a CDSS by characterizing it from three layers and discuss the algorithms in each layer. Also we address the applications of CDSSs in a few real scenarios and analyze the accuracy of a CDSS in consideration of the potential conflicts when using multiple clinical practice guidelines concurrently. Finally, we compare the system performance in our design with that in the other design schemes. Our study shows that our proposed design can achieve a clinical decision in a shorter time than the other designs, while ensuring a high level of system accuracy. Hindawi 2017 2017-03-08 /pmc/articles/PMC5361053/ /pubmed/28373881 http://dx.doi.org/10.1155/2017/1562919 Text en Copyright © 2017 Aihua Fan et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Fan, Aihua
Lin, Di
Tang, Yu
Clinical Decision Support Systems for Comorbidity: Architecture, Algorithms, and Applications
title Clinical Decision Support Systems for Comorbidity: Architecture, Algorithms, and Applications
title_full Clinical Decision Support Systems for Comorbidity: Architecture, Algorithms, and Applications
title_fullStr Clinical Decision Support Systems for Comorbidity: Architecture, Algorithms, and Applications
title_full_unstemmed Clinical Decision Support Systems for Comorbidity: Architecture, Algorithms, and Applications
title_short Clinical Decision Support Systems for Comorbidity: Architecture, Algorithms, and Applications
title_sort clinical decision support systems for comorbidity: architecture, algorithms, and applications
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5361053/
https://www.ncbi.nlm.nih.gov/pubmed/28373881
http://dx.doi.org/10.1155/2017/1562919
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