Biomedical Holistic Ontology for People with Rare Diseases

Laia Subirats, Jordi Conesa and Manuel Armayones
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Laia Subirats: Eurecat, Centre Tecnològic de Catalunya, C/Bilbao, 72, 08005 Barcelona, Spain
Jordi Conesa: eHealth Center, Universitat Oberta de Catalunya, Rambla del Poblenou, 156, 08018 Barcelona, Spain
Manuel Armayones: eHealth Center, Universitat Oberta de Catalunya, Rambla del Poblenou, 156, 08018 Barcelona, Spain

IJERPH, 2020, vol. 17, issue 17, 1-11

Abstract: This research provides a biomedical ontology to adequately represent the information necessary to manage a person with a disease in the context of a specific patient. A bottom-up approach was used to build the ontology, best ontology practices described in the literature were followed and the minimum information to reference an external ontology term (MIREOT) methodology was used to add external terms of other ontologies when possible. Public data of rare diseases from rare associations were used to build the ontology. In addition, sentiment analysis was performed in the standardized data using the Python library Textblob. A new holistic ontology was built, which models 25 real scenarios of people with rare diseases. We conclude that a comprehensive profile of patients is needed in biomedical ontologies. The generated code is openly available, so this research is partially reproducible. Depending on the knowledge needed, several views of the ontology should be generated. Links to other ontologies should be used more often to model the knowledge more precisely and improve flexibility. The proposed holistic ontology has many benefits, such as a more standardized computation of sentiment analysis between attributes.

Keywords: biomedical ontologies; medical health records; interoperability; sentiment analysis (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
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