Biography
Lei is affiliated with the "AI for Healthcare'' CHI Lab led by Prof David Clifton, and currently leads a group of 3-4 researchers in the Nuffield Department of Population Health. She also leads analytical work in the Pandemic Science Institute on effective pandemic preparedness and response. Lei is a senior advisor of the NIHR Research Support Service team, which provides free advice on research design to researchers.
Lei was awarded a PhD in Statistical Machine Learning in 2007 from UMIST (now the University of Manchester), and subsequently worked as a post-doctoral researcher and then a medical statistician in the University of Oxford. She enjoys painting watercolours and playing violin, both amateurishly, in her spare time.
Other Information
Statistical and machine learning expertise in large-scale clinical records.
Most Recent Publications
Bridging the generalisation gap: synthetic data generation for multi-site clinical model validation
Bridging the generalisation gap: synthetic data generation for multi-site clinical model validation
Implementation framework for AI deployment at scale in healthcare systems.
Implementation framework for AI deployment at scale in healthcare systems.
Dysregulated immune proteins in plasma in the UK Biobank predict Multiple Myeloma 12 years before clinical diagnosis
Dysregulated immune proteins in plasma in the UK Biobank predict Multiple Myeloma 12 years before clinical diagnosis
Application of large language models in medicine
Application of large language models in medicine
Bridging the Generalisation Gap: Synthetic Data Generation for Multi-Site Clinical Model Validation
Bridging the Generalisation Gap: Synthetic Data Generation for Multi-Site Clinical Model Validation
Research Interests
Lei's research interests are in the field of medical statistics and AI, for large-scale observational studies and electronic health records.
Most Recent Publications
Bridging the generalisation gap: synthetic data generation for multi-site clinical model validation
Bridging the generalisation gap: synthetic data generation for multi-site clinical model validation
Implementation framework for AI deployment at scale in healthcare systems.
Implementation framework for AI deployment at scale in healthcare systems.
Dysregulated immune proteins in plasma in the UK Biobank predict Multiple Myeloma 12 years before clinical diagnosis
Dysregulated immune proteins in plasma in the UK Biobank predict Multiple Myeloma 12 years before clinical diagnosis
Application of large language models in medicine
Application of large language models in medicine
Bridging the Generalisation Gap: Synthetic Data Generation for Multi-Site Clinical Model Validation
Bridging the Generalisation Gap: Synthetic Data Generation for Multi-Site Clinical Model Validation
