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
Aligning, autoencoding and prompting large language models for novel disease reporting
Aligning, autoencoding and prompting large language models for novel disease reporting
At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods
At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods
Figure 3 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank
Figure 3 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank
Supplementary Table S2 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank
Supplementary Table S2 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank
Supplementary Table S5 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank
Supplementary Table S5 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank
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
Aligning, autoencoding and prompting large language models for novel disease reporting
Aligning, autoencoding and prompting large language models for novel disease reporting
At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods
At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods
Figure 3 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank
Figure 3 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank
Supplementary Table S2 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank
Supplementary Table S2 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank
Supplementary Table S5 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank
Supplementary Table S5 from Assessing the Value of Incorporating a Polygenic Risk Score with Nongenetic Factors for Predicting Breast Cancer Diagnosis in the UK Biobank
