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
A multimodal automated deep learning-based model for predicting biochemical recurrence of prostate cancer following prostatectomy from baseline MRI, Presurgical clinical covariates
A multimodal automated deep learning-based model for predicting biochemical recurrence of prostate cancer following prostatectomy from baseline MRI, Presurgical clinical covariates
A collaborative large language model for drug analysis
A collaborative large language model for drug analysis
Learning Across the Divide: Personalised Federated Learning for Robust Clinical Modelling under Data-View Heterogeneity
Learning Across the Divide: Personalised Federated Learning for Robust Clinical Modelling under Data-View Heterogeneity
Dynamic Beat-to-Beat Measurements of Blood Pressure Using Multimodal Physiological Signals and a Hybrid CNN-LSTM Model
Dynamic Beat-to-Beat Measurements of Blood Pressure Using Multimodal Physiological Signals and a Hybrid CNN-LSTM Model
Beyond correlations: the necessity and the challenges of causal AI
Beyond correlations: the necessity and the challenges of causal AI
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
A multimodal automated deep learning-based model for predicting biochemical recurrence of prostate cancer following prostatectomy from baseline MRI, Presurgical clinical covariates
A multimodal automated deep learning-based model for predicting biochemical recurrence of prostate cancer following prostatectomy from baseline MRI, Presurgical clinical covariates
A collaborative large language model for drug analysis
A collaborative large language model for drug analysis
Learning Across the Divide: Personalised Federated Learning for Robust Clinical Modelling under Data-View Heterogeneity
Learning Across the Divide: Personalised Federated Learning for Robust Clinical Modelling under Data-View Heterogeneity
Dynamic Beat-to-Beat Measurements of Blood Pressure Using Multimodal Physiological Signals and a Hybrid CNN-LSTM Model
Dynamic Beat-to-Beat Measurements of Blood Pressure Using Multimodal Physiological Signals and a Hybrid CNN-LSTM Model
Beyond correlations: the necessity and the challenges of causal AI
Beyond correlations: the necessity and the challenges of causal AI
