I am very excited to join the Translational Epidemiology Unit (TEU) as a medical statistician where I will explore risk factors for chronic diseases aiming for disease prevention and intervention development. I will provide full statistical and programming expertise, manage large-scale data, construct advanced statistical models and present research findings.
View an introduction to how to use UKBiobank data on the Translational Epidemiology Unit webpage.
From 2018 to 2020, I worked as a clinical trial statistician in the Thames Valley Clinical Trials Unit (TVCTU) where I engaged in many interventional studies across different fields, from determining the impact of a psychology intervention on child development to investigating the pain relief effect of a treatment for osteoarthritis. I worked closely with multidisciplinary teams and provided statistical support to the development of trials from design to publication.
After graduating in BSc Mathematics from the University of Bristol, I attended an MSc statistics course in Imperial College London for full time training on my interests, medical statistics and machine learning. For my dissertation, I joined the London Institute of Medical Sciences creating and implementing innovative deep learning models to predict survival outcomes of patients who suffer from pulmonary hypertension using their longitudinal 3D cardiac motion. My experience really makes me realise the importance and fast development of statistics in medical research, which boots my dedication to medical statistics field.
Combining machine learning with Cox models to identify predictors for incident post-menopausal breast cancer in the UK Biobank.
Liu X. et al, (2023), Scientific reports, 13
Polygenic Risk of Prediabetes, Undiagnosed Diabetes, and Incident Type 2 Diabetes Stratified by Diabetes Risk Factors.
Liu X. et al, (2023), Journal of the Endocrine Society, 7
Effects of training parents in dialogic book‐sharing: The Early‐Years Provision in Children's Centers (EPICC) study
Murray L. et al, (2023), Early Childhood Research Quarterly, 62, 1 - 16
Assessing agreement between different polygenic risk scores in the UK Biobank.
Clifton L. et al, (2022), Scientific reports, 12
Are polygenic risk scores for systolic blood pressure and LDL-cholesterol associated with treatment effectiveness, and clinical outcomes among those on treatment?
Tapela NM. et al, (2022), European journal of preventive cardiology, 29, 925 - 937