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

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.

Methods

Radiation Oncology anatomical and target volumes were categorized in anatomical and treatment planning classes. International delineation guidelines specific to radiation oncology were used for lymph nodes areas and target v

SUBMITTER: Bibault JE 

PROVIDER: S-EPMC5774757 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature