Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

From multisource data to clinical decision aids in radiation oncology: the need for a clinical data science community

Kazmierska, Joanna, Hope, Andrew, Spezi, Emiliano ORCID: https://orcid.org/0000-0002-1452-8813, Beddar, Sam, Nailon, William H., Osong, Biche, Ankolekar, Anshu, Choudhury, Ananya, Dekker, Andre, Redalen, Kathrine Røe and Traverso, Alberto 2020. From multisource data to clinical decision aids in radiation oncology: the need for a clinical data science community. Radiotherapy and Oncology 153 , pp. 43-54. 10.1016/j.radonc.2020.09.054

[thumbnail of PIIS016781402030829X.pdf]
Preview
PDF - Published Version
Available under License Creative Commons Attribution No Derivatives.

Download (1MB) | Preview

Abstract

Big data are no longer an obstacle; now, by using artificial intelligence (AI), previously undiscovered knowledge can be found in massive data collections. The radiation oncology clinic daily produces a large amount of multisource data and metadata during its routine clinical and research activities. These data involve multiple stakeholders and users. Because of a lack of interoperability, most of these data remain unused, and powerful insights that could improve patient care are lost. Changing the paradigm by introducing powerful AI analytics and a common vision for empowering big data in radiation oncology is imperative. However, this can only be achieved by creating a clinical data science community in radiation oncology. In this work, we present why such a community is needed to translate multisource data into clinical decision aids.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Engineering
Additional Information: This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
Publisher: Elsevier
ISSN: 0167-8140
Date of First Compliant Deposit: 29 October 2020
Date of Acceptance: 20 September 2020
Last Modified: 05 May 2023 03:04
URI: https://orca.cardiff.ac.uk/id/eprint/136006

Citation Data

Cited 9 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics