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Yearb Med Inform 2015; 24(01): 134-136
DOI: 10.15265/IY-2015-038
Original Article
Georg Thieme Verlag KG Stuttgart

Knowledge Representation and Management. From Ontology to Annotation

Findings from the Yearbook 2015 Section on Knowledge Representation and Management
J. Charlet
1   AP-HP, Dept. of Clinical Research and Development, Paris, France
2   INSERM, U1142, LIMICS, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), Villetaneuse, France
,
S.J. Darmoni
2   INSERM, U1142, LIMICS, Paris, France; Sorbonne Universités, UPMC Univ Paris 06, UMR_S 1142, LIMICS, Paris, France; Université Paris 13, Sorbonne Paris Cité, LIMICS, (UMR_S 1142), Villetaneuse, France
3   Department of Biomedical Informatics, Rouen University Hospital, Normandy & TIBS, LITIS EA 4108, Institute for Research and Innovation in Biomedicine, Rouen, France
,
Section Editors for the IMIA Yearbook Section on Knowledge Representation and Management › Author Affiliations
Further Information

Publication History

13 August 2015

Publication Date:
10 March 2018 (online)

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Summary

Objective: To summarize the best papers in the field of Knowledge Representation and Management (KRM).

Methods: A comprehensive review of medical informatics literature was performed to select some of the most interesting papers of KRM published in 2014.

Results: Four articles were selected, two focused on annotation and information retrieval using an ontology. The two others focused mainly on ontologies, one dealing with the usage of a temporal ontology in order to analyze the content of narrative document, one describing a methodology for building multi-lingual ontologies.

Conclusion: Semantic models began to show their efficiency, coupled with annotation tools.

Keywords

Ontology - knowledge representation - annotation
 

  • References

  • 1 Choi S, Choi J, Yoo S, Kim H, Lee Y. Semantic concept-enriched dependence model for medical information retrieval. J Biomed Inform 2014; Feb 47: 18-27.
    CrossrefPubMedGoogle Scholar
  • 2 Funk C, Baumgartner Jr W, Garcia B, Roeder C, Bada M, Cohen KB. et al. Large-scale biomedical concept recognition: an evaluation of current automatic annotators and their parameters. BMC Bioinformatics 2014; 15: 59.
    CrossrefPubMedGoogle Scholar
  • 3 Clark K, Sharma D, Qin R, Chute CG, Tao C. A use case study on late stent thrombosis for ontology-based temporal reasoning and analysis. J Biomed Semantics 2014; Dec 11 5 (01) 49.
    CrossrefPubMedGoogle Scholar
  • 4 Dramé K, Diallo G, Delva F, Dartigues JF, Mouillet E, Salamon R. et al. Reuse of termino-ontological resources and text corpora for building a multilingual domain ontology: an application to Alzheimer’s disease. J Biomed Inform 2014; Apr 48: 171-82.
    CrossrefPubMedGoogle Scholar
  • 5 Nichols BN, Mejino JL, Detwiler LT, Nilsen TT, Martone ME, Turner JA. et al. Neuroanatomical domain of the foundational model of anatomy ontology. J Biomed Semantics 2014; Jan 8 5 (01) 1.
    CrossrefPubMedGoogle Scholar
  • 6 López-García P, Lependu P, Musen M, Illarramendi A. Cross-domain targeted ontology subsets for annotation: the case of SNOMED CORE and RxNorm. J Biomed Inform 2014; Feb 47: 105-11.
    CrossrefPubMedGoogle Scholar
  • 7 Doulaverakis C, Nikolaidis G, Kleontas A, Kompatsiaris I. Panacea, a semantic-enabled drug recommendations discovery framework. J Biomed Semantics 2014; Mar 6 5 (01) 13.
    CrossrefPubMedGoogle Scholar
  • 8 Anguita A, García-Remesal M, de la Iglesia D, Graf N, Maojo V. Toward a view-oriented approach for aligning RDF-based biomedical repositories. Methods Inf Med 2015; 54 (01) 50-5.
    Article in Thieme ConnectPubMedGoogle Scholar
  • 9 Gøeg KR, Cornet R, Andersen SK. Clustering clinical models from local electronic health records based on semantic similarity. J. Biomed Inform 2015; Apr 54: 294-304.
    PubMedGoogle Scholar
  • 10 Chakrabarti C, Jones TB, Luger GF, Xu JF, Turner MD, Laird AR. et al. Statistical algorithms for ontology-based annotation of scientific literature. J Biomed Semantics 2014; Jun 3 5 (01) Proceedings of the Bio-Ontologies Spec Interest G S2.
    CrossrefPubMedGoogle Scholar
  • 11 Harispe S, Sánchez D, Ranwez S, Janaqi S, Montmain J. A framework for unifying ontology-based semantic similarity measures: a study in the biomedical domain. J Biomed Inform 2014; Apr 48: 38-53.
    CrossrefPubMedGoogle Scholar
  • 12 Palombi O, Ulliana F, Favier V, Léon JC, Rousset MC. My Corporis Fabrica: an ontology-based tool for reasoning and querying on complex anatomical models. J Biomed Semantics 2014; May 6 5: 20.
    CrossrefPubMedGoogle Scholar
  • 13 Soldatova LN, Nadis D, King RD, Basu PS, Haddi E, Baumlé V. et al. EXACT2: the semantics of biomedical protocols. BMC Bioinformatics 2014; 15 (14) S5.
    PubMedGoogle Scholar
  • 14 Kim TY, Hardiker N, Coenen A. Inter-terminology mapping of nursing problems. J Biomed Inform 2014; Jun 49: 213-20.
    CrossrefPubMedGoogle Scholar
  • 15 Xue N, Doellinger M, Fripp J, Ho CP, Surowiec RK, Schwarz R. Automatic model-based semantic registration of multimodal MRI knee data. J Magn Reson Imaging 2015; Mar 41 (03) 633-44.
    CrossrefPubMedGoogle Scholar
  • 16 Baneyx A, Charlet J, Jaulent MC. Building an ontology of pulmonary diseases with natural language processing tools using textual corpora. Int J Med Inform 2007; Feb-Mar 76 2-3 208-15.
    CrossrefPubMedGoogle Scholar