BSc (Hons), MB & BChir (Cantab), MRCS, FRCA
DPhil Student & Consultant Anaesthetist
Research focusing on the evaluation of assistive AI in 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). He undertakes this alongside his clinical role as a Consultant Anaesthetist in the Aneurin Bevan University Health Board.
His research focuses on the role of assistive artificial intelligence in the identification of anatomical structures on ultrasound. He works with Intelligent Ultrasound Limited (IUL), a company which develops software and simulation devices to facilitate ultrasound scanning. Initial DPhil work is focusing on the evaluation of AnatomyGuide, developed by IUL (https://doi.org/10.1111/anaes.15212 and https://doi.org/10.1002/ca.23742).
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. He finished training in August 2020 and has since worked as a consultant and began his DPhil.
Exploring the utility of assistive artificial intelligence for ultrasound scanning in regional anesthesia.
Bowness JS. et al, (2022), Reg Anesth Pain Med
Artificial Intelligence: Innovation to Assist in the Identification of Sono-anatomy for Ultrasound-Guided Regional Anaesthesia.
Lloyd J. et al, (2022), Adv Exp Med Biol, 1356, 117 - 140
International consensus on anatomical structures to identify on ultrasound for the performance of basic blocks in ultrasound-guided regional anesthesia.
Bowness JS. et al, (2021), Reg Anesth Pain Med
AI real-time color overlay of sonoanatomy.
Bowness J. and Laurent DB-S., (2021), J Anesth