David Clifton
Professor of Clinical Machine Learning
David Clifton is Professor of Clinical Machine Learning in the Department of Engineering Science of the University of Oxford. He is a Research Fellow of the Royal Academy of Engineering, Visiting Chair in AI for Healthcare at the University of Manchester, and a Fellow of Fudan University, China. He runs the Computational Health Informatics Lab within the Department of Engineering Science, which has sites in Oxford (at the Institute of Biomedical Engineering) and China (in the Oxford Suzhou Centre for Advanced Research).
David studied Information Engineering at Oxford's Department of Engineering Science. His previous research resulted in patented systems for jet-engine health monitoring, used with the engines of the Airbus A380, the Boeing 787 "Dreamliner", and the Eurofighter Typhoon. Since 2008, he has focused mostly on healthcare applications, and his current research focuses on the development of machine learning for tracking the health of complex systems. Patents arising from his collaborative research have been commercialised via university spin-out companies OBS Medical, Oxehealth, and Sensyne Health. He holds an EPSRC "Grand Challenge" fellowship for "future leaders in healthcare", and was jointly awarded the inaugural Vice-Chancellor's Prize for Innovation, for interdisciplinary research.
Recent publications
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Status of Digital Health Technology Adoption in 5 Vietnamese Hospitals: Cross-Sectional Assessment
Tran DM. et al, (2025), JMIR Formative Research, 9, e53483 - e53483
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AI-assisted In silico Trial for the Optimization of Osmotherapy after Ischaemic Stroke
Chen X. et al, (2025), IEEE Journal of Biomedical and Health Informatics
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Aligning, Autoencoding and Prompting Large Language Models for Novel Disease Reporting
Liu F. et al, (2025), IEEE Transactions on Pattern Analysis and Machine Intelligence, 1 - 12
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CC-SAM: SAM with Cross-Feature Attention and Context for Ultrasound Image Segmentation
Gowda SN. and Clifton DA., (2025), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 15103 LNCS, 108 - 124
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Denoising Reuse: Exploiting Inter-frame Motion Consistency for Efficient Video Generation
Wang C. et al, (2025), IEEE Transactions on Circuits and Systems for Video Technology