Xiaomin Zhong

Xiaomin (Billy) Zhong’s work focuses on leveraging large-scale health data to inform public health policy and clinical care, with a particular emphasis on cancer. 

Billy has conducted published studies exploring complex disease associations and developing clinical risk prediction models. He has used population-level datasets, including primary and secondary care records, to investigate the impacts of events such as the COVID-19 pandemic on disease burden and outcomes. His research spans areas such as cardiovascular disease, infectious disease, and cancer. 

Billy has contributed to healthcare-driven projects using linked data to create risk prediction models. These models generate personalised risk scores based on factors like age, sex, clinical and medication history, ethnicity, and socioeconomic status. These refined models have been integrated into a Knowledge Support System (KSS) to aid clinical decision-making. 

His work involves collaborations with research groups, including Oxford University Hospitals (OUH), the University of Manchester, and the UK Health Security Agency (UKHSA). He uses linked datasets from sources such as the Clinical Practice Research Datalink (CPRD), OpenSAFELY, and the British Heart Foundation Data Science Centre, (BHF DSC) as well as clinical trials like ASCEND PLUS. 

Billy holds a PhD in Health Informatics and an MSc in Health Data Science from the University of Manchester, and a BSc from Peking University, China. He teaches on the Health Data Science MSc at Manchester and supervises MSc Global Health Science and Epidemiology projects at Oxford Population Health.