Surface semantics from electronic medical records with knowledge graph technologies
In this talk, I will share our experience and lessons learnt from applying artificial intelligence technologies at several large UK hospitals, aiming at making health data available to understand disease and find ways to prevent, treat and cure them. I will introduce a health informatics toolkit - CogStack-SemEHR in transforming, integrating and analysing near real-time electronic medical records. This talk will give examples on how knowledge graph technologies are useful and necessary in surfacing semantics in applications of natural language processing and network analysis for answering clinical questions. It will end with discussions on challenges and our thoughts on future directions of knowledge graphs in healthcare.
Honghan Wu
Dr Honghan Wu is a lecturer in health informatics at Institute of Health Informatics, University College London, UK and holds a Rutherford Fellowship funded by Medical Research Council UK. Dr Wu leads a health informatics group (https://knowlab.github.io). He co-founded and co-leads Edinburgh Clinical Natural Language Processing Group (https://www.ed.ac.uk/usher/clinical-natural-language-processing). He has a background in computing science (PhD in semantic search) and his current research interest is in using text technologies and Knowledge Graph techniques to analyse electronic health records (EHRs).