Child cancer follow-up ontology and information system


Abstract:

An increase in chronic diseases in Danish healthcare can be explained by the corresponding increase of population longevity. Health professionals will not be able to keep up with treating those diseases, due to the many existing and new cases of chronic diseases. This results in mistakes in treatment processes, compensations to patients due to medical negligence and duplication of work and effort. In order to address a solution for healthcare practitioners, a small subgroup of patients and diseases is chosen from all chronic diseases. Namely, children diagnosed with cancer. This research brings the methodology for child cancer treatment plan that produces an ontology to create a conceptual model and a database model. To construct the ontology, the "methontology" method is used as a structured approach for the ontology process. The method guides the ontology developer from scratch to building a complete model. The ontology is developed in two phases. In the first phase, research from other countries and process models are reviewed and the generic model is built from this research. The generic model is adapted to the ontology for the Danish hospitals including the NOPHO-ALL 2008 protocol. To develop the ontology, a data dictionary is first proposed. Then, the relationships between concepts are identified and verified: the oriented graph, where nodes are concepts and oriented edges are dependence relationships, where the definition of the concept at the origin of the edge depends on the concept at the destination of the edge, must be a directed acyclic graph. Finally, the ontology resulting from the previous steps is implemented in Protégé-OWL. The conceptual model follows directly and univocally from the ontology: an entity-relationship diagram in UML notation. © 2013 WIT Press.

Año de publicación:

2013

Keywords:

  • ERD
  • Child cancer follow-up
  • ontology
  • Information System

Fuente:

googlegoogle
scopusscopus

Tipo de documento:

Conference Object

Estado:

Acceso abierto

Áreas de conocimiento:

  • Ontología
  • Ciencias de la computación

Áreas temáticas:

  • Medicina y salud
  • Funcionamiento de bibliotecas y archivos
  • Enfermedades