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AI in Population Health

AI in Population Health provides powerful tools to enhance clinical outcomes by producing improved diagnostic speed and accurate, enabling earlier and more personalized treatment options. 

Research within this cluster focuses on the interface between AI and Population health. It is only by crossing fields that we are able to develop a cohesive picture of key population health issues, what we can do to detect and manage them, and how we can apply AI based technology to enhance clinical outcomes and improve quality life. 

Core Themes: 

  • Development of novel AI empowered image-based risk prediction tools to improve diagnostic speed and accuracy, enabling earlier treatment and prevention of disease (e.g., diabetes related complications). 
  • Epidemiological modelling of electronic health records to enhance AI based risk prediction understanding, including big data approaches. 
  • Developing novel AI algorithms for analysing complex healthcare data to improve the accuracy, efficiency, and accessibility of healthcare delivery.  
  • Developing self-supervised learning and generative adversarial network models to tackle the challenges of insufficient labels and missing data in various healthcare data. 
Name Project title Project information
Robyn Tapp The long-term effectiveness of a peer-led lifestyle intervention program on diabetes progression and cardiovascular risk: The Kerala Diabetes Prevention Program in India. To stem the growing epidemic of chronic diseases in rapidly developing countries like India that face significant resource constraints, prevention programs are needed in rural communities where most people still live.
Dr Jiangtao Wang   Compressive Population Health: Cost-Effective Profiling of Prevalence for Multiple Non-Communicable Diseases via Health Data Science.  This project proposes a novel paradigm, called compressive population health (CPH for short), to reduce the data collection cost during the profiling of prevalence to the maximum extent. 

Cluster Lead

Professor Robyn Tapp 

Robyn Tapp is a Professor in Epidemiology and Evidence-Based Healthcare and leads the AI in the Population Health cluster at Coventry University. Robyn has throughout her career translated population-based data into significant relevance to the individual who will benefit from primary and secondary prevention of diabetes and its severe complications.

Cluster Members

Dr Jiangtao Wang 

Jiangtao Wang is an Associate Professor with strong international reputation for his research on Ubiquitous Computing, Mobile Crowdsensing/Crowdsourcing, and Health Data Science. He collaborates closely with clinicians, environment engineers, industrial partners, and government policy makers to move ubiquitous computing and AI technology into the pathways of health care, in terms of both individual and population level. With several novel research perspectives, Jiangtao has achieved a number of top conference and journal publications. Jiangtao also serves for the journal editorial board such as Personal and Ubiquitous Computing, Frontiers in Sustainable Cities, etc, and PC members of multiple top international conferences. 

Dr Kim Bul

Dr. Kim Bul is an Assistant Professor with extensive experience in the development and effectiveness of digital health interventions. She has a specific interest in using serious games and gamification elements to increase engagement with health interventions. In 2019 she joined the Centre for Intelligent Healthcare at Coventry University to pursue her research interest in digital health and more specifically in serious gaming, gamification, (mental) health, behaviour change and interventions. She led the scientific programme of our EIT Digital Health summer school in 2022 and is currently a guest editor for Frontiers in Digital Health and International Journal of Environmental and Public Health Research. She is also a co-lead of the digital health working group and leads the research enriched learning activities within the Centre for Intelligent Healthcare.

Visiting Professor

Professor Annice Mukherjee (Honorary)

Professor Mukherjee has a national and international profile in clinical endocrinology which has spanned two decades. She has an international reputation and track record in academic endocrine research, having won several awards including the prestigious Merck Senior Fellow Award at the American Endocrine Society. Dr Mukherjee Honorary Professorship at Coventry University is to continue her research endeavours alongside Professor Robyn Tapp and Dr Maxine Whelan, focused on chronic disease prevention for midlife women. 

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