Shi Xin:Using Big Data For Effective Health Management — Early Diagnosis, Intervention & Prevention

Time: January 9, 2021, 17:30

Venue: Zoom

Speaker: Professor Shi Xin

Topic: Using Big Data For Effective Health Management — Early Diagnosis, Intervention & Prevention 

Abstract:

Health is the most important demand for humans. Long and healthy life is one of the primary research subjects in human health research. However, it is difficult to accurately access health status at a very early stage, with the aim of determining appropriate interventions to maintain good health and wellbeing. Therefore, it is essential to optimise human health management polices and assess the risk factors associated with health status.

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 using non-clinical and clinical linkage data.Some symptoms that could indicate potential advanced disease or chronic disease can often be ignored or missed. This will lead to serious delay in clinical diagnosis and timely treatment intervention. Subsequently, it will increase the medical treatment costs as well as increasing the patient’s physical, mental and financial burden. 

Our study aims to develop a systematic approach which integrates statistical and artificial intelligent health big data modelling into optimal health management decision-making with mobile application. By developing statistical modelling method for health big data on early diagnosis, prevention and intervention, we are developing a multi stage delay-time model to investigate risk factors and predict heath status at an earlier stage of disease/illness progression using linked clinical and non-clinical data. 

In this talk, we will our recent research outcomes and discuss the challenges for the future study.

Guest Speaker: 

Professor Shi Xin

Dr Xin Shi is a Prof in Applied Statistics and a doctoral supervisor at Manchester Metropolitan University in the United Kingdom. He has served as the Associate Dean of China Affairs at the Faculty of Business Law and Director of the China Centre; Vice President of the Karaganda Medical Universityof Kazakhstan; concurrently Director of the Shanghai University Commercial Big Data and Applied Statistics Research Centre. Xin’s active research focus on health big data research since he graduated from the University of Salford with a PhD in Statistics in 2008. He has served in many medical schools in the UK. He was awarded the Chartered Statistician (CStat) and Fellow (Fellow) by the Royal Statistical Society, and the Treasurer of Manchester Group of the Royal Statistical Society. Dr Shi is the editor-in- chief and deputy editor-in-chief of a number of international journals and a funding application reviewer for UNESCO projects. He was elected as a member of the European Academy of Sciences and Arts in 2019 and becomes the youngest Chinese member in the academy.

Xin’s main research in the past few years has been devoted to big data and health management and risk analysis (Health Management and Risk Assessment using Big Data). The research results have been recognised by the British 2014 REF judges with international high-level scientific research results. In May 2019, at the invitation of the prestigious Astana Economic Forum (Astana Economic Forum), on behalf of the Ministry of Health of Kazakhstan, Xin made an important speech on The Impact of Big Data on the National Health System of Kazakhstan. In 2019, he was invited to give special lectures at Stanford University in the United States, the University of Windsor in Canada, the City University of Hong Kong and the Chinese University of Hong Kong. In recent years, his research has focused on the use of non-clinical and linked big data to predict clinical outcomes and decisions for personalized health management, such as early cancer diagnosis. His current research projects include: a) the use of non- clinical big data for cancer early diagnose; b) the application of immersive technology in medical treatment; c) the international calculation standard for happiness measurement; d) human health management, especially the delay time of chronic diseases Model; e) Addict research related to drug use; f) Health/smoking big data and survival analysis. He has extensive health-related big data research experience, including linked data from the United Kingdom, China, Japan andBrazil.

In the past five years, Dr Shi has successfully hosted and participated in funded research projects of more than £900,000. In particular, he participated in the first major international cooperation project of the National Natural Science Foundation of China in the direction of health management (2 million RMB 2015-2019). It is important that Xin further improved and extended the traditional methods of reliability/maintenance research to business management and human life, and applied them to big data in health management and employment research.

Shi Xin's research is to use non-clinical and clinical data, based on our knowledge of human health and disease prevention, to monitor, predict, intervene and control the process and methods of health risk factors. His research can not only support the early diagnosis of clinical diseases, but also find some symptoms that may indicate hidden disease, which has reduced the serious delay in clinical diagnosis and treatment intervention. As a result, it will greatly reduce medical expenses and the physical,psychological and economic burden of patients. From the perspective of theoretical methods, Xin’s research has made a major breakthrough in the systematic research methods of health big data, especially in data collection, analysis and application sustainability and integrated development.