Lei Clifton
Official Fellow in AI & ML, Reuben College
Statistics and AI for clinical studies
My research interest is at the interface of medical statistics and AI, with over 20 years of research experience.
I am the Programme Director of the MSc in Applied Digital Health, where I am also module leader and lecturer, working alongside the Academic Directors, Profs. John Powell and Catherine Pope.
My research focuses on a wide range of methodology, including foundation models (and large language models) for healthcare, disease prediction, and the fusion of AI with medical statistics. Much of this work collaborates closely with the "AI for Healthcare" group in the Department of Engineering Science, where I also hold an affiliation.
After studying engineering and machine learning, I did my postdoctoral training at the Department of Engineering Science (2009-14), before training as a medical statistician under Prof. Doug Altman at the Centre for Statistics in Medicine (2014-18). Subsequently, I was team leader in the Nuffield Department of Population Health (2019-24), where I led a programme of research in translational epidemiology.
When at home, I can be found painting watercolours, practising yoga, and making noise on the violin with friends.
Recent publications
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Bridging the Generalisation Gap: Synthetic Data Generation for Multi-Site Clinical Model Validation
Conference paper
Segal B. et al, (2025)
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Implementation framework for AI deployment at scale in healthcare systems
Journal article
Adnan HS. et al, (2025), iScience, 28
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Dysregulated immune proteins in plasma in the UK Biobank predict Multiple Myeloma 12 years before clinical diagnosis.
Journal article
Fieggen J. et al, (2025), Blood Adv
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Navigating Severe Class Imbalance in Population Cohort Data
Conference paper
Fieggen J. et al, (2025)
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Bridging the Generalisation Gap: Synthetic Data Generation for
Multi-Site Clinical Model Validation
Preprint
Segal B. et al, (2025)
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