A knowledge graph representation of baseline characteristics for the Dutch proton therapy research registry

M. Sloep; P. Kalendralis; A. Choudhury; L. Seyben; J. Snel; N.M. George; M. Veening; J.A. Langendijk; A. Dekker; J. van Soest; R. Fijten

doi:10.1016/j.ctro.2021.10.001

A knowledge graph representation of baseline characteristics for the Dutch proton therapy research registry

M. Sloep, P. Kalendralis, A. Choudhury, L. Seyben, J. Snel, N.M. George, M. Veening, J.A. Langendijk, A. Dekker, J. van Soest, R. Fijten^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › Academic › peer-review

Abstract

Cancer registries collect multisource data and provide valuable information that can lead to unique research opportunities. In the Netherlands, a registry and model-based approach (MBA) are used for the selection of patients that are eligible for proton therapy. We collected baseline characteristics including demographic, clinical, tumour and treatment information. These data were transformed into a machine readable format using the FAIR (Findable, Accessible, Interoperable, Reusable) data principles and resulted in a knowledge graph with baseline characteristics of proton therapy patients. With this approach, we enable the possibility of linking external data sources and optimal flexibility to easily adapt the data structure of the existing knowledge graph to the needs of the clinic.

Original language	English
Pages (from-to)	93-96
Number of pages	4
Journal	Clinical and Translational Radiation Oncology
Volume	31
DOIs	https://doi.org/10.1016/j.ctro.2021.10.001
Publication status	Published - 1 Nov 2021

Keywords

RADIOTHERAPY

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10.1016/j.ctro.2021.10.001Licence: CC BY

Cite this

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title = "A knowledge graph representation of baseline characteristics for the Dutch proton therapy research registry",

abstract = "Cancer registries collect multisource data and provide valuable information that can lead to unique research opportunities. In the Netherlands, a registry and model-based approach (MBA) are used for the selection of patients that are eligible for proton therapy. We collected baseline characteristics including demographic, clinical, tumour and treatment information. These data were transformed into a machine readable format using the FAIR (Findable, Accessible, Interoperable, Reusable) data principles and resulted in a knowledge graph with baseline characteristics of proton therapy patients. With this approach, we enable the possibility of linking external data sources and optimal flexibility to easily adapt the data structure of the existing knowledge graph to the needs of the clinic.",

keywords = "RADIOTHERAPY",

author = "M. Sloep and P. Kalendralis and A. Choudhury and L. Seyben and J. Snel and N.M. George and M. Veening and J.A. Langendijk and A. Dekker and {van Soest}, J. and R. Fijten",

note = "Funding Information: We want to thank the Dutch Cancer Society KWF 30943405N for funding the development of the ProTRAIT infrastructure and subsequent proton therapy research repository. Publisher Copyright: {\textcopyright} 2021 The Authors",

year = "2021",

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doi = "10.1016/j.ctro.2021.10.001",

language = "English",

volume = "31",

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T1 - A knowledge graph representation of baseline characteristics for the Dutch proton therapy research registry

AU - Sloep, M.

AU - Kalendralis, P.

AU - Choudhury, A.

AU - Seyben, L.

AU - Snel, J.

AU - George, N.M.

AU - Veening, M.

AU - Langendijk, J.A.

AU - Dekker, A.

AU - van Soest, J.

AU - Fijten, R.

N1 - Funding Information: We want to thank the Dutch Cancer Society KWF 30943405N for funding the development of the ProTRAIT infrastructure and subsequent proton therapy research repository. Publisher Copyright: © 2021 The Authors

PY - 2021/11/1

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N2 - Cancer registries collect multisource data and provide valuable information that can lead to unique research opportunities. In the Netherlands, a registry and model-based approach (MBA) are used for the selection of patients that are eligible for proton therapy. We collected baseline characteristics including demographic, clinical, tumour and treatment information. These data were transformed into a machine readable format using the FAIR (Findable, Accessible, Interoperable, Reusable) data principles and resulted in a knowledge graph with baseline characteristics of proton therapy patients. With this approach, we enable the possibility of linking external data sources and optimal flexibility to easily adapt the data structure of the existing knowledge graph to the needs of the clinic.

AB - Cancer registries collect multisource data and provide valuable information that can lead to unique research opportunities. In the Netherlands, a registry and model-based approach (MBA) are used for the selection of patients that are eligible for proton therapy. We collected baseline characteristics including demographic, clinical, tumour and treatment information. These data were transformed into a machine readable format using the FAIR (Findable, Accessible, Interoperable, Reusable) data principles and resulted in a knowledge graph with baseline characteristics of proton therapy patients. With this approach, we enable the possibility of linking external data sources and optimal flexibility to easily adapt the data structure of the existing knowledge graph to the needs of the clinic.

KW - RADIOTHERAPY

U2 - 10.1016/j.ctro.2021.10.001

DO - 10.1016/j.ctro.2021.10.001

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SN - 2405-6308

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