In Medical physics ; h5-index 59.0
The registration of multi-source radiation oncology data is a time consuming and labour intensive procedure. The standardisation of data collection offers the possibility for the acquisition of quality data for research and clinical purposes. With this study we present an overview of the different tumour group data lists in the Dutch national proton therapy registry. Furthermore, as a representative example of the workings of these different tumour specific knowledge graphs, we present the FAIR (Findable, Accessible, Interoperable, Reusable) data principles-compliant knowledge graph approach describing the head and neck tumour variables using radiotherapy domain ontologies and semantic web technologies. Our goal is to provide the radiotherapy community with a flexible and interoperable data model for data exchange between centres. We highlight data variables that are needed for models used in the model-based approach (MBA), which ensures a fair selection of patients that will benefit most from proton therapy. This article is protected by copyright. All rights reserved.
Kalendralis Petros, Sloep Matthijs, Choudhury Ananya, Seyben Lerau, Snel Jasper, George Nibin Moni, Veugen Joeri, Veening Martijn, Langendijk Johannes A, Dekker Andre, van Soest Johan, Fijten Rianne
2022-Dec-09
FAIR, artificial intelligence, knowledge graph, proton therapy
