Labeling for Big Data in radiation oncology: The Radiation Oncology Structures ontology.

Journal: PloS one
PMID: 29351341

Abstract

PURPOSE: Leveraging Electronic Health Records (EHR) and Oncology Information Systems (OIS) has great potential to generate hypotheses for cancer treatment, since they directly provide medical data on a large scale. In order to gather a significant amount of patients with a high level of clinical details, multicenter studies are necessary. A challenge in creating high quality Big Data studies involving several treatment centers is the lack of semantic interoperability between data sources. We present the ontology we developed to address this issue.

Authors

  • Jean-Emmanuel Bibault
    Radiation Oncology Department, Georges Pompidou European Hospital, Assistance Publique - Hôpitaux de Paris, Paris Descartes University, Paris Sorbonne Cité, Paris, France; INSERM UMR 1138 Team 22: Information Sciences to support Personalized Medicine, Paris Descartes University, Sorbonne Paris Cité, Paris, France. Electronic address: jean-emmanuel.bibault@aphp.fr.
  • Eric Zapletal
    University Hospital Georges Pompidou (HEGP); AP-HP, Paris, France.
  • Bastien Rance
    AP-HP, University Hospital Georges Pompidou; INSERM, UMR_S 1138, Centre de Recherche des Cordeliers, Paris, France.
  • Philippe Giraud
    Radiation Oncology Department, Georges Pompidou European Hospital, Assistance Publique - Hôpitaux de Paris, Paris Descartes University, Paris Sorbonne Cité, Paris, France.
  • Anita Burgun
    Hôpital Necker-Enfants malades, AP-HP, Paris, France.

Keywords

External Resources

Popular Topics
Recent Journals