Concept-based versus Realism-based Approach to Represent Neuroimaging Observations

Emna Amdouni, Bernard Gibaud

Abstract

The aim of this paper is to argue why we should adopt a realism-based approach to describe neuroimaging features that are involved in clinical assessments rather than a concept-based approach. This work is a part of a proposal aiming at making explicit the meaning of neuroimaging observations via realism-based ontologies.

References

  1. Brandon, B., Vinay, C., Nikhil, D., 2013. A Vocabulary of Topological and Containment Relations for a Practical Biological Ontology. Spat. Inf. Theory, Lecture Notes in Computer Science 418-437.
  2. Ceusters, W., Elkin, P., Smith, B., 2006. Referent tracking: the problem of negative findings. Stud. Health Technol. Inform. 124, 741-746.
  3. Ceusters, W., Smith, B., 2005. Tracking referents in electronic health records. Stud. Health Technol. Inform. 116, 71-76.
  4. Cimino, J.J., 2006. In defense of the Desiderata. J. Biomed. Inform. 39, 299-306..
  5. Clunie, D.A., 2007. DICOM Structured Reporting and Cancer Clinical Trials Results. Cancer Inform. 4, 33- 56.
  6. Frederick Nat. Lab for Cancer Research, 2014. VASARI Research Project - The Cancer Imaging Archive (TCIA) [WWW Document]. URL https://wiki.cancerimagingarchive.net/display/Public/ VASARI+Research+Project (accessed 7.14.16).
  7. Grenon, P., Smith, B., Goldberg, L., 2003. Biodynamic ontology: applying BFO in the biomedical domain. Stud. Health Technol. Inform. 102, 20-38.
  8. Rector, A., Nowlan, W., Kay, S., 1991. Foundations for an electronic medical record. Methods Inf. Med. 30, 179- 186.
  9. Rubin, D.L., Willrett, D., O'Connor, M.J., Hage, C., Kurtz, C., Moreira, D.A., 2014. Automated Tracking of Quantitative Assessments of Tumor Burden in Clinical Trials. Transl. Oncol. 7, 23-35.
  10. Rubin, D., Mongkolwat, P., Channin, D., 2008. A semantic image annotation model to enable integrative translational research. Summit Transl. Bioinforma. 2009, 106-110.
  11. Smith, B., 2006. From concepts to clinical reality: an essay on the benchmarking of biomedical terminologies. J. Biomed. Inform. 39, 288-298.
  12. Smith, B., Ceusters, W., Klagges, B., Köhler, J., Kumar, A., Lomax, J., Mungall, C., Neuhaus, F., Rector, A.L., Rosse, C., 2005. Relations in biomedical ontologies. Genome Biol. 6, R46.
  13. Smith, B., Kusnierczyk, W., Schober, D., Ceusters, W., 2006. Towards a Reference Terminology for Ontology Research and Development in the Biomedical Domain.
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Paper Citation


in Harvard Style

Amdouni E. and Gibaud B. (2016). Concept-based versus Realism-based Approach to Represent Neuroimaging Observations . In Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD, (IC3K 2016) ISBN 978-989-758-203-5, pages 179-185. DOI: 10.5220/0006084401790185


in Bibtex Style

@conference{keod16,
author={Emna Amdouni and Bernard Gibaud},
title={Concept-based versus Realism-based Approach to Represent Neuroimaging Observations},
booktitle={Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD, (IC3K 2016)},
year={2016},
pages={179-185},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006084401790185},
isbn={978-989-758-203-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 2: KEOD, (IC3K 2016)
TI - Concept-based versus Realism-based Approach to Represent Neuroimaging Observations
SN - 978-989-758-203-5
AU - Amdouni E.
AU - Gibaud B.
PY - 2016
SP - 179
EP - 185
DO - 10.5220/0006084401790185