TY  - JOUR
TI  - Artificial intelligence in paediatric radiology: Future opportunities
AV  - public
VL  - 94
Y1  - 2020/09/17/
N1  - This version is the version of record. For information on re-use, please refer to the publisher?s terms and conditions.
IS  - 1117
ID  - discovery10113199
N2  - Artificial intelligence (AI) has received widespread and growing interest in healthcare, as a method to save time, cost and improve efficiencies. The high-performance statistics and diagnostic accuracies reported by using AI algorithms (with respect to predefined reference standards), particularly from image pattern recognition studies, have resulted in extensive applications proposed for clinical radiology, especially for enhanced image interpretation. Whilst certain sub-speciality areas in radiology, such as those relating to cancer screening, have received wide-spread attention in the media and scientific community, children's imaging has been hitherto neglected.In this article, we discuss a variety of possible 'use cases' in paediatric radiology from a patient pathway perspective where AI has either been implemented or shown early-stage feasibility, while also taking inspiration from the adult literature to propose potential areas for future development. We aim to demonstrate how a 'future, enhanced paediatric radiology service' could operate and to stimulate further discussion with avenues for research.
UR  - https://doi.org/10.1259/bjr.20200975
JF  - The British Journal of Radiology
A1  - Davendralingam, N
A1  - Sebire, NJ
A1  - Arthurs, OJ
A1  - Shelmerdine, SC
ER  -