Artificial intelligence in paediatric radiology: Future opportunities.

Journal: The British journal of radiology
Published Date:

Abstract

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.

Authors

  • Natasha Davendralingam
    Department of Radiology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK.
  • Neil J Sebire
    Health Data Research UK, London, UK.
  • Owen J Arthurs
    UCL Great Ormond Street Institute of Child Health, University College London, London WC1E 6BT, United Kingdom.
  • Susan C Shelmerdine
    UCL Great Ormond Street Institute of Child Health, University College London, London WC1E 6BT, United Kingdom.