Dr Stephen Weng

School of Medicine, University of Nottingham

I am an Assistant Professor of Integrated Epidemiology and Data Science who leads the data science research within the Primary Care Stratified Medicine Research Group at the University of Nottingham. I integrate traditional epidemiological methods and study design with new informatics-based approaches, harnessing and interrogating "big health care data" from electronic medical records for the purpose of risk prediction modelling, phenotyping chronic diseases, data science methods research, and translation of stratified medicine into primary care. I started out in life sciences in the US, with my undergraduate degree in Biological Sciences at the University of Virginia, followed by a Master in Public Health and PhD in Applied Epidemiology both at the University of Nottingham in the UK. I have previous industry experience and have also held an NIHR career launching fellowship from the National School for Primary Care Research to explore novel methodologies to improve risk prediction in primary care.

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Machine-learning in prognostic research using routine health care data

The poster child for machine-learning or artificial intelligence in healthcare is in imaging. This seminar will explore the application of the machine-learning algorithms for prognostic research, that is prediction and classification of disease from using health care data such as electronic health records, large population cohorts, and clinical trials. This session will demonstrate several concrete examples of these ML approaches using different sources of health care data.