HeNeCOn: An ontology for integrative research in Head and Neck cancer.

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.

Data analytics for predicting quality of life changes in head and neck cancer survivors: a scoping review.

Head and neck cancer is the seventh most common cancer worldwide. The incidence of this cancer is increasing, but at the same time, the cancer-related mortality rate has decreased over time, leaving more head and neck cancer survivors. More emphasis is needed on quality-of-life research in the head and neck cancer field to improve their daily lives and reduce the disease and treatment response burden. To achieve this, we conducted a scoping review to find and learn which predictors and data analysis techniques have been used in previous studies. This work is undertaken in the context of the BD4QoL EU Research project.

Communication platform for biosensor-based sleep management applications.

This paper presents the architecture of a complete communications platform for biosensor-based applications in the domain of sleep disorders. It covers from the direct communication with the sensors themselves to the most remote application modules. It has been divided into three levels: BAN (Body Area Network), LAN (Local Area Network) and WAN (Wide Area Network), and it uses wireless communications at all levels of the architecture.