TY - JOUR
T1 - HeNeCOn
T2 - An ontology for integrative research in Head and Neck cancer
AU - the BD2Decide Consortium
AU - Hernández, Liss
AU - Estévez-Priego, Estefanía
AU - López-Pérez, Laura
AU - Fernanda Cabrera-Umpiérrez, María
AU - Arredondo, María Teresa
AU - Fico, Giuseppe
AU - Poli, Tito
AU - Rossi, Silvia
AU - Martinelli, Elena
AU - Licitra, Lisa
AU - Cavalieri, Stefano
AU - De Cecco, Loris
AU - Canevari, Silvana
AU - Scheckenbach, Kathrin
AU - Brakenhoff, Ruud H.
AU - Nauta, Irene
AU - Hoebers, Frank J.P.
AU - Wesseling, Frederik W.R.
AU - Trama, Annalisa
AU - Gatta, Gemma
N1 - Funding Information: This work has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreements BD2Decide No. 689715 and BD4QoL No. 875192. Publisher Copyright: © 2023 The Author(s)
PY - 2024/1
Y1 - 2024/1
N2 - Background: Head and Neck Cancer (HNC) has a high incidence and prevalence in the worldwide population. The broad terminology associated with these diseases and their multimodality treatments generates large amounts of heterogeneous clinical data, which motivates the construction of a high-quality harmonization model to standardize this multi-source clinical data in terms of format and semantics. The use of ontologies and semantic techniques is a well-known approach to face this challenge. Objective: This work aims to provide a clinically reliable data model for HNC processes during all phases of the disease: prognosis, treatment, and follow-up. Therefore, we built the first ontology specifically focused on the HNC domain, named HeNeCOn (Head and Neck Cancer Ontology). Methods: First, an annotated dataset was established to provide a formal reference description of HNC. Then, 170 clinical variables were organized into a taxonomy, and later expanded and mapped to formalize and integrate multiple databases into the HeNeCOn ontology. The outcomes of this iterative process were reviewed and validated by clinicians and statisticians. Results: HeNeCOn is an ontology consisting of 502 classes, a taxonomy with a hierarchical structure, semantic definitions of 283 medical terms and detailed relations between them, which can be used as a tool for information extraction and knowledge management. Conclusion: HeNeCOn is a reusable, extendible and standardized ontology which establishes a reference data model for terminology structure and standard definitions in the Head and Neck Cancer domain. This ontology allows handling both current and newly generated knowledge in Head and Neck cancer research, by means of data linking and mapping with other public ontologies.
AB - Background: Head and Neck Cancer (HNC) has a high incidence and prevalence in the worldwide population. The broad terminology associated with these diseases and their multimodality treatments generates large amounts of heterogeneous clinical data, which motivates the construction of a high-quality harmonization model to standardize this multi-source clinical data in terms of format and semantics. The use of ontologies and semantic techniques is a well-known approach to face this challenge. Objective: This work aims to provide a clinically reliable data model for HNC processes during all phases of the disease: prognosis, treatment, and follow-up. Therefore, we built the first ontology specifically focused on the HNC domain, named HeNeCOn (Head and Neck Cancer Ontology). Methods: First, an annotated dataset was established to provide a formal reference description of HNC. Then, 170 clinical variables were organized into a taxonomy, and later expanded and mapped to formalize and integrate multiple databases into the HeNeCOn ontology. The outcomes of this iterative process were reviewed and validated by clinicians and statisticians. Results: HeNeCOn is an ontology consisting of 502 classes, a taxonomy with a hierarchical structure, semantic definitions of 283 medical terms and detailed relations between them, which can be used as a tool for information extraction and knowledge management. Conclusion: HeNeCOn is a reusable, extendible and standardized ontology which establishes a reference data model for terminology structure and standard definitions in the Head and Neck Cancer domain. This ontology allows handling both current and newly generated knowledge in Head and Neck cancer research, by means of data linking and mapping with other public ontologies.
KW - Clinical information system
KW - Data modeling
KW - Data standardization
KW - Head and neck cancer
KW - Ontology
KW - Ontology-based knowledge
KW - Protégé
UR - http://www.scopus.com/inward/record.url?scp=85177995568&partnerID=8YFLogxK
U2 - https://doi.org/10.1016/j.ijmedinf.2023.105284
DO - https://doi.org/10.1016/j.ijmedinf.2023.105284
M3 - Article
C2 - 37981440
SN - 1386-5056
VL - 181
JO - International Journal of Medical Informatics
JF - International Journal of Medical Informatics
M1 - 105284
ER -