Abstract: Adoption of electronic health records to document extensive clinical information brings with it the opportunity to utilise that information to support clinical decisions. In this talk, I will discuss both these opportunities and the challenges that we face when working with real-world clinical data, and introduce some of the strategies that we are adopting to make this data more usable, and to model it effectively. I will specifically discuss several examples of how we are applying natural language processing to transform clinical documentation into structured data, and for use in clinical surveillance and prediction applications.
Bio: Professor Karin Verspoor is Dean of the School of Computing Technologies at RMIT University in Melbourne, Australia and a Fellow of the Australasian Institute of Digital Health. Karin’s research primarily focuses on the use of artificial intelligence methods to enable biological discovery and clinical decision support, through extraction information from clinical texts and the biomedical literature and machine learning-based modelling. In addition to roles in academia and government research facilities in the US and Australia, Karin spent 5 years in technology start-ups developing AI and NLP systems.