The validated-DB complies with ethics regulations and represents the population studied. It is accessible by neuroradiologists willing to use information provided by MRS to help in the non-invasive diagnosis of brain tumours.

We present an agent-based distributed decision support system for the diagnosis and prognosis of brain tumours developed by the HealthAgents project. HealthAgents is a European Union funded research project, which aims to enhance the classification of brain tumours using such a decision support system based on intelligent agents to securely connect a network of clinical centres. The HealthAgents system is implementing novel pattern recognition discrimination methods, in order to analyse in vivo Magnetic HealthAgents intends not only to apply forefront agent technology to the biomedical field, but also develop the HealthAgents network, a globally distributed information and knowledge repository for brain tumour diagnosis and prognosis.

The eTUMOUR (eT) multi-centre project gathered in vivo and ex vivo magnetic resonance (MR) data, as well as transcriptomic and clinical information from brain tumour patients, with the purpose of improving the diagnostic and prognostic evaluation of future patients. In order to carry this out, among other work, a database—the eTDB—was developed. In addition to complex permission rules and software and management quality control (QC), it was necessary to develop anonymization, processing and data visualization tools for the data uploaded. It was also necessary to develop sophisticated curation strategies that involved on one hand, dedicated fields for QC-generated meta-data and specialized queries and global permissions for senior curators and on the other, to establish a set of metrics to quantify its contents. The indispensable dataset (ID), completeness and pairedness indices were set. The database contains 1317 cases created as a result of the eT project and 304 from a previous project, INTERPRET. The number of cases fulfilling the ID was 656. Completeness and pairedness were heterogeneous, depending on the data type involved.

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This paper introduces HealthAgents, an EC-funded research project to improve the classification of brain tumours through multi-agent decision support over a distributed network of local databases or Data Marts. HealthAgents will not only develop new pattern recognition methods for a distributed classification and analysis of in vivo MRS and ex vivo/in vitro HRMAS

This paper focuses on the problem of representing, in a meaningful way, the knowledge involved in the HealthAgents project. Our work is motivated by the complexity of representing Electronic Healthcare Records in a consistent manner. We present HADOM (HealthAgents Domain Ontology) which conceptualises the required HealthAgents information and propose describing the sources knowledge by the means of Conceptual Graphs (CGs). This allows to build upon the existing ontology permit-ting for modularity and flexibility. The novelty of our approach lies in the ease with which CGs can be placed above other formalisms and their potential for optimised querying and retrieval.

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