Contact information
(01865) 231510
Colleges
James S Bowness
BSc (Hons), MB & BChir (Cantab), DPhil (Oxon), MRCS, FRCA
Consultant Anaesthetist
Research focusing on the evaluation of assistive AI for the interpretation of ultrasound in regional anaesthesia
James moved to the Nuffield Department of Clinical Neurosciences in October 2020, to undertake a DPhil supervised by Associate Professor Helen Higham (NDCN) and Professor Alison Noble (IBME). His clinical role as a Consultant Anaesthetist at University College London Hospitals NHS Foundation Trust.
His research focuses on the role of assistive artificial intelligence in the acquisition and interpretation of ultrasound images for regional anaesthesia. He works with Intelligent Ultrasound Limited, a company which develops software and simulation devices to facilitate ultrasound scanning.
He completed his undergraduate training at the University of St Andrews (BSc (Hons), Medical Sciences) and Magdalene College, University of Cambridge (MB BChir, Clinical Medicine). After a brief time in surgery he crossed the blood-brain barrier to anaesthetics and trained as an Academic Clinical Lecturer in the University of Dundee/East of Scotland Deanery.
Recent publications
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Research priorities in regional anaesthesia: an international Delphi study.
Journal article
Ferry J. et al, (2024), Br J Anaesth
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Artificial intelligence for ultrasound scanning in regional anaesthesia: a scoping review of the evidence from multiple disciplines
Journal article
Bowness JS. et al, (2024), British Journal of Anaesthesia
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Leading in the development, standardised evaluation, and adoption of artificial intelligence in clinical practice: regional anaesthesia as an example.
Journal article
Bowness JS. et al, (2024), Br J Anaesth
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Assistive artificial intelligence for enhanced patient access to ultrasound-guided regional anaesthesia.
Journal article
Bowness JS. et al, (2023), Br J Anaesth
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Variability between human experts and artificial intelligence in identification of anatomical structures by ultrasound in regional anaesthesia: a framework for evaluation of assistive artificial intelligence
Journal article
Bowness JS. et al, (2023), British Journal of Anaesthesia
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Recommendations for anatomical structures to identify on ultrasound for the performance of intermediate and advanced blocks in ultrasound-guided regional anesthesia.
Journal article
Ashken T. et al, (2022), Reg Anesth Pain Med, 47, 762 - 772
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Evaluation of the impact of assistive artificial intelligence on ultrasound scanning for regional anaesthesia.
Journal article
Bowness JS. et al, (2022), Br J Anaesth
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Assistive artificial intelligence for ultrasound image interpretation in regional anaesthesia: an external validation study.
Journal article
Bowness JS. et al, (2022), Br J Anaesth
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Exploring the utility of assistive artificial intelligence for ultrasound scanning in regional anesthesia.
Journal article
Bowness JS. et al, (2022), Reg Anesth Pain Med
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Artificial Intelligence: Innovation to Assist in the Identification of Sono-anatomy for Ultrasound-Guided Regional Anaesthesia.
Journal article
Lloyd J. et al, (2022), Adv Exp Med Biol, 1356, 117 - 140