Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/115858
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Type: Journal article
Title: A Web-accessible distributed data warehouse for brain tumour diagnosis
Author: Estanyol, F.
Rafael, X.
Roset, R.
Lurgi, M.
Mier, M.
Lluch-Ariet, M.
Citation: Knowledge Engineering Review, 2011; 26(3):329-351
Publisher: Cambridge University Press
Issue Date: 2011
ISSN: 0269-8889
1469-8005
Statement of
Responsibility: 
Francesc Estanyol, Xavier Rafael, Roman Roset, Miguel Lurgi, Mariola Mier and Magi Lluch-Ariet
Abstract: Currently, biological databases (DBs) are a common tool to complement the research of a wide range of biomedical disciplines, but there are only a few specialized medical DBs for human brain tumour magnetic resonance spectroscopy (MRS) data; they typically store a limited range of biological data (i.e. clinical information, magnetic resonance imaging and MRS data) and are not offered as open-source Structured Query Language relational DB schemas. We present a novel approach to biological DBs: a distributed Web-accessible DB for storing and managing clinical and biomedical data related to brain tumours from different clinical centres. This tool is designed for multi-platform systems with dissimilar DB management systems. Being the main data repository of the HealthAgents (HA) project, it uses multi-agent technology and allows the centres to share data and obtain diagnosis classifications from other centres distributed around the world in a reliable way. The HA project aims to create an agent-based distributed decision support system (DSS) to assist doctors to provide a brain tumour diagnosis and prognosis. The HA DB enables the DSS to totally integrate with its Graphical User Interface to perform classifications with the stored data and visualize the results using the HA distributed agents framework. This new feature converts the system presented in the first application in the world to combine a storage and management tool for brain tumour data and a complete Web-based DSS to obtain automatic diagnosis.
Rights: © Cambridge University Press, 2011
RMID: 0030019708
DOI: 10.1017/S0269888911000142
Appears in Collections:Medicine publications

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