2008 21st IEEE International Symposium on Computer-Based Medical Systems 2008
DOI: 10.1109/cbms.2008.17
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The ACGT Master Ontology on Cancer – A New Terminology Source for Oncological Practice

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Cited by 10 publications
(7 citation statements)
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“…In our experiments, we have selected as global schema the semantic core of the ACGT platform: the ACGT Master Ontology on Cancer (MO) [28]. This ontology covers the domain of clinical trials on cancer, so we built ad-hoc databases in this field presenting the different cases of heterogeneity included on purpose.…”
Section: Experiments and Resultsmentioning
confidence: 99%
“…In our experiments, we have selected as global schema the semantic core of the ACGT platform: the ACGT Master Ontology on Cancer (MO) [28]. This ontology covers the domain of clinical trials on cancer, so we built ad-hoc databases in this field presenting the different cases of heterogeneity included on purpose.…”
Section: Experiments and Resultsmentioning
confidence: 99%
“…ACGT [15] is an open environment for supporting clinical trials and related research through the use of grid-enabled tools and infrastructure, and to some extent is a precursor to the research conducted in ContraCancrum. The Oncosimulator [16] is an advanced information system, developed by the EU FP6 ACGT project, which aims to simulate the response of tumours and affected normal tissues to therapeutic schemes based on clinical, imaging, histopathological and molecular data of a given cancer patient, in order to optimize cancer treatment on a patientindividualized basis.…”
Section: Review Of the State Of The Artmentioning
confidence: 99%
“…The Wisconsin Breast Cancer Dataset (WBC) [37] ontology has used as a case study to create a new breast cancer ontology engine that contains two phases. In phase 1, this algorithm matches the searched knowledge and prepares the rules whether searched knowledge is available in the datasets or not.…”
Section: Breast Cancer: Benign and Malignant Cancer Medical Ontologymentioning
confidence: 99%
“… Existing datasets ontologies has used to develop a new algorithm for breast cancer patients without human interactions. For this purpose, the Wisconsin Breast Cancer Dataset (WBC) [37] has used as a case study to create a new ontology engine which contains two phases. In phase 1, this algorithm will match the searched knowledge and will prepare the rules whether searched knowledge is available in the datasets or not.…”
Section: B Specific Medical Ontologiesmentioning
confidence: 99%