Laborie, LB; Naidoo, J; Pace, E; Ciet, P; Eade, C; Wagner, MW; Huisman, TAGM; Shelmerdine, SC
(2023)
European Society of Paediatric Radiology Artificial Intelligence taskforce: a new taskforce for the digital age.
Pediatr Radiol, 53 (4).
pp. 576-580.
ISSN 1432-1998
https://doi.org/10.1007/s00247-022-05426-3
SGUL Authors: Shelmerdine, Susan Cheng
Abstract
A new task force dedicated to artificial intelligence (AI) with respect to paediatric radiology was created in 2021 at the International Paediatric Radiology (IPR) meeting in Rome, Italy (a joint society meeting by the European Society of Pediatric Radiology [ESPR] and the Society for Pediatric Radiology [SPR]). The concept of a separate task force dedicated to AI was borne from an ESPR-led international survey of health care professionals' opinions, expectations and concerns regarding AI integration within children's imaging departments. In this survey, the majority (> 80%) of ESPR respondents supported the creation of a task force and helped define our key objectives. These include providing educational content about AI relevant for paediatric radiologists, brainstorming ideas for future projects and collaborating on AI-related studies with respect to collating data sets, de-identifying images and engaging in multi-case, multi-reader studies. This manuscript outlines the starting point of the ESPR AI task force and where we wish to go.
Item Type: |
Article
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Additional Information: |
© The Author(s) 2022
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
Keywords: |
Artificial intelligence, Children, Education, Machine learning, Radiology, Artificial intelligence, Children, Education, Machine learning, Radiology, 1114 Paediatrics and Reproductive Medicine, Nuclear Medicine & Medical Imaging |
SGUL Research Institute / Research Centre: |
Academic Structure > Institute of Medical, Biomedical and Allied Health Education (IMBE) Academic Structure > Institute of Medical, Biomedical and Allied Health Education (IMBE) > Centre for Clinical Education (INMECE ) |
Journal or Publication Title: |
Pediatr Radiol |
ISSN: |
1432-1998 |
Language: |
eng |
Dates: |
Date | Event |
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April 2023 | Published | 22 June 2022 | Published Online | 3 June 2022 | Accepted |
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Publisher License: |
Creative Commons: Attribution 4.0 |
Projects: |
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PubMed ID: |
35731260 |
Web of Science ID: |
WOS:000814488500002 |
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Go to PubMed abstract |
URI: |
https://openaccess.sgul.ac.uk/id/eprint/114916 |
Publisher's version: |
https://doi.org/10.1007/s00247-022-05426-3 |
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