Reader in Applied Statistics and Director of Manchester Met China Centre, Manchester Metropolitan University
Title: Big data for Business and Health—Early Diagnosis, Intervention and Prevention
Good health is the number one demand among all demands of human being. Long and healthy life is one of the primary research subjects in human health research. It is well known that human health is closely related to human behaviour and environment, social economic status, aging and genetic susceptibility, thus it is important to study these factors and their relationships to human health. Human health management is the process and means for health risk factors monitoring, prognostics, intervention and control based on our knowledge on human health and prevention and the data generated from past surveys and clinical trials. The research on this subject is far from perfect, and there are indeed needs both in methodologies and applications to be researched. Correct and timely human health management is extremely important to the protection and improvement of human health. This research shall try to develop, based on the data from survey, clinical and disease counts databases, models of health risk analysis, life prediction and health assessment methods, public health surveillance approaches, in order to provide the theoretical support to government in medical and social policy making and to individuals and population in their health management.
Dr. Xin Shi is a Reader in Applied Statistics at Business School of Manchester Metropolitan University. He is a Guest Professor at Beijing University of Aeronautics and Astronautics in China. He has been awarded for Chartered Statistician by the Royal Statistical Society UK. During 2007 to 2009, he was working as a postdoc in the direction of evidence-based medicine in the medical school of University of Sheffield, UK. Meanwhile, he worked as a research assistant in social statistics in the University of Manchester.
His research areas cover business analytics, health big data, personalized health management, life course modelling. Xin has expertise on survival modelling, generalized linear models, Meta-analysis, Evidence synthesis analysis, longitudinal data, time series, decision models, health economics, and optimization theory. The applications can be found in prognostic health management, medical science, population health management, sports and health, and management of own business. In the last 5 years, Xin has been awarded a several research grant from external and internal research bodies on business analytics. Currently he is the co-investigator of a £200k research project funded by National Nature Science Funder Council in China (NSFC) to investigate the population health management and risk analysis cross the worldwide.