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Real-Time Clinical Decision Support System with Data Stream Mining

This research aims to describe a new design of data stream mining system that can analyze medical data stream and make real-time prediction. The motivation of the research is due to a growing concern of combining software technology and medical functions for the development of software application t...

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Detalles Bibliográficos
Autores principales: Zhang, Yang, Fong, Simon, Fiaidhi, Jinan, Mohammed, Sabah
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3407674/
https://www.ncbi.nlm.nih.gov/pubmed/22851884
http://dx.doi.org/10.1155/2012/580186
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author Zhang, Yang
Fong, Simon
Fiaidhi, Jinan
Mohammed, Sabah
author_facet Zhang, Yang
Fong, Simon
Fiaidhi, Jinan
Mohammed, Sabah
author_sort Zhang, Yang
collection PubMed
description This research aims to describe a new design of data stream mining system that can analyze medical data stream and make real-time prediction. The motivation of the research is due to a growing concern of combining software technology and medical functions for the development of software application that can be used in medical field of chronic disease prognosis and diagnosis, children healthcare, diabetes diagnosis, and so forth. Most of the existing software technologies are case-based data mining systems. They only can analyze finite and structured data set and can only work well in their early years and can hardly meet today's medical requirement. In this paper, we describe a clinical-support-system based data stream mining technology; the design has taken into account all the shortcomings of the existing clinical support systems.
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spelling pubmed-34076742012-07-31 Real-Time Clinical Decision Support System with Data Stream Mining Zhang, Yang Fong, Simon Fiaidhi, Jinan Mohammed, Sabah J Biomed Biotechnol Research Article This research aims to describe a new design of data stream mining system that can analyze medical data stream and make real-time prediction. The motivation of the research is due to a growing concern of combining software technology and medical functions for the development of software application that can be used in medical field of chronic disease prognosis and diagnosis, children healthcare, diabetes diagnosis, and so forth. Most of the existing software technologies are case-based data mining systems. They only can analyze finite and structured data set and can only work well in their early years and can hardly meet today's medical requirement. In this paper, we describe a clinical-support-system based data stream mining technology; the design has taken into account all the shortcomings of the existing clinical support systems. Hindawi Publishing Corporation 2012 2012-07-18 /pmc/articles/PMC3407674/ /pubmed/22851884 http://dx.doi.org/10.1155/2012/580186 Text en Copyright © 2012 Yang Zhang 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
Zhang, Yang
Fong, Simon
Fiaidhi, Jinan
Mohammed, Sabah
Real-Time Clinical Decision Support System with Data Stream Mining
title Real-Time Clinical Decision Support System with Data Stream Mining
title_full Real-Time Clinical Decision Support System with Data Stream Mining
title_fullStr Real-Time Clinical Decision Support System with Data Stream Mining
title_full_unstemmed Real-Time Clinical Decision Support System with Data Stream Mining
title_short Real-Time Clinical Decision Support System with Data Stream Mining
title_sort real-time clinical decision support system with data stream mining
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3407674/
https://www.ncbi.nlm.nih.gov/pubmed/22851884
http://dx.doi.org/10.1155/2012/580186
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