This talk will explore the application of the epidemiological and data science methods for the prediction and classification of disease using health care data such as electronic health records, large population cohorts, and clinical trial registries. I will demonstrate several concrete examples of these approaches in my own research, with a particular focus on cardiovascular diseases, using sources in data both in the UK and internationally.
Dr Stephen Weng is an Assistant Professor of Epidemiology and Data Science who leads the data science research within the Primary Care Stratified Medicine Research Group at the University of Nottingham. He integrates traditional epidemiological methods and study design with new informatics-based approaches, harnessing and interrogating "big health care data" here in the UK and internationally for the purpose of risk prediction modelling, phenotyping chronic diseases, data science methods research, and translation of stratified medicine into primary care. He started out in life sciences in the US, with his 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. He has previous industry experience and has 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.
This talk is being held as part of the Big Data Epidemiology course which is part of the Evidence-Based Health Care Programme.
This is a free event and members of the public are welcome to attend.