Facilitating the use of routine data to evaluate artificial intelligence solutions: lessons from the NIHR/RCR data curation workshop.

S C Shelmerdine¹, S E Hickman², N Jackson³, D Cronheim⁴, J Taylor⁵, A J Swift⁶, M Thurston⁷, A Davies⁸, S Ather⁹, S Doran¹⁰, J Nash¹¹, A G Rockall¹²,

¹Department of Clinical Radiology, Great Ormond Street Hospital, London, UK; UCL Great Ormond Street Institute of Child Health, Great Ormond Street Hospital for Children, London, UK; NIHR Great Ormond Street Hospital Biomedical Research Centre, London, UK. Electronic address: susan.shelmerdine@gosh.nhs.uk.

²Barts Health NHS Trust, The Royal London Hospital, 80 Newark Street, London, UK.

³NIHR RDNCC (Research Delivery Network Coordinating Centre), UK.

⁴NIHR Patient Public Involvement and Engagement, UK.

⁵Nuclear Medicine & 3DLab, Sheffield Teaching Hospitals, Sheffield, UK.

⁶Department of Clinical Medicine, University of Sheffield, Sheffield, UK.

⁷Department of Radiology, University Hospitals Plymouth NHS Trust, Plymouth, PL6 8DH, UK.

⁸The Association of British HealthTech Industries (ABHI), Suite 2, 4(th) Floor, 1 Duchess Street, London, W1W 6AN, UK.

⁹Oxford University Hospitals NHS Foundation Trust, Oxford, UK.

¹⁰National Cancer Imaging Translational Accelerator, London, UK; Division of Radiotherapy and Imaging, The Institute of Cancer Research, London, UK.

¹¹Kheiron Medical Technologies, 112-116 Old St., London EC1V 9BG, UK.

¹²Department of Surgery & Cancer, Imperial College London, London, UK.

PubMed DOI

Abstract

Radiology currently stands at the forefront of artificial intelligence (AI) development and deployment over many other medical subspecialities within the scope of both research and clinical practice. Given this current leadership position, it is imperative that we foster collaboration and knowledge sharing to ensure the ethical, responsible and effective continued progress of AI technologies in ou…

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