Proposition of an Ontology of Diseases and Their Signs from Medical Ontologies Integration

To assist medical diagnosis, we propose a federation
of several existing and open medical ontologies and terminologies.
The goal is to merge the strengths of all these resources to provide
clinicians the access to a variety of shared knowledges that can
facilitate identification and association of human diseases and all of
their available characteristic signs such as symptoms and clinical
signs. This work results to an integration model loaded from target
known ontologies of the bioportal platform such as DOID, MESH,
and SNOMED for diseases selection, SYMP, and CSSO for all
existing signs.

Authors:

• Adama Sow
• Abdoulaye Guiss´e
• Oumar Niang

Keywords:

• Medical decision
• medical ontologies
• ontologies integration
• linked data
• knowledge ingeneering
• e-health system.

References:

[1] Charlet J, Declerck G., Dhombres F., Gayet P., Miroux P., Vandenbussche
P.: Construire une ontologie m´edicale pour la recherche d’information:
probl´ematiques terminologiques et de mod´elisation. IC 2012.
[2] Anbarasi M. S., Naveen P., Selvaganapathi S., Mohamed Nowsath Ali
I., Ontology Based Medical Diagnosis Decision Support System, In
International Journal of Engineering Research and Technology (IJERT),
2013.
[3] Robert Hoehndorf, Michel Dumontier and Georgios V. Gkoutos,
Evaluation of research in biomedical ontologies, In Bioinformatics. vol
14. No 6. 696-712, 2012.
[4] Jos´e A., Reye S-Ortiz, Ana L. Jimenez, Jaime Cater, Cesar A.
Malend´es, Ontology-based Knowledge Representation for Supporting
Medical Decisions, Recherche in Computer Science, 2013.
[5] Mohammed, Osama and Benlamri, Rachid and Fong, Simon, Building
a Diseases Symptoms Ontology for Medical Diagnosis: An Integrative
Approach, D´ecembre 2012, IEEE International Conference on Future
Generation Commnication Technology (FGCT 2012).
[6] Hoehndorf, Robert and Schofield, Paul N. and Gkoutos, Georgios V., The
role of ontologies in biological and biomedical research: a functional
perspective, In Briefings in Bioinformatics Journal, 2015
[7] Alexander P. Cox, Patrick L. Ray, Mark Jensen, Alexander D. Diehl,
Defining ’sign’ and ’symptom’, IWOOD 2014 Workshop, In ICBO,
Houston, TX, USA, October 6-7, 2014.
[8] Lynn, Schriml and Arze, Cesar and al., Disease Ontology: A backbone
for disease semantic integration, Nucleic acids research, 2011.
[9] Whetzel PL, Noy NF, Shah NH, Alexander PR, al., BioPortal:
enhanced functionality via new Web services from the National Center
for Biomedical Ontology to access and use ontologies in software
applications, Nucleic Acids Res. 2011 Jul, 39(Web Server issue):W541-5,
Epub 2011 Jun 14.
[10] Salvadores M, Horridge M, Alexander PR, Fergerson RW, Musen
MA, and Noy NF, Using SPARQL to Query BioPortal Ontologies and
Metadata, International Semantic Web Conference (Boston US) LNCS
7650, pp 180195, 2012.
[11] Cornet, Ronald and De Keize, Nicolette, Forty years of SNOMED: a
literature review, In First European Conference on SNOMED CT, 1-3
October 2006, Copenhagen, Denmark.
[12] Smith, Barry and Ashburner, Michael and al., The OBO Foundry:
coordinated evolution of ontologies to support biomedical data
integration, In Nature Biotechnology, 2007, Volume 25.
[13] Olivier Bodenreider, The Unified Medical Language System (UMLS):
integrating biomedical terminology, in Nucleic Acids Research, 2004, Vol.
32.
[14] Karen Patrias and Dan Wendling, Citing Medicine, 2nd edition, In
National Library of Medicine, National Institutes of Health Bethesda
(MD): National Library of Medicine (US); 2007.