September 2016

How can we capture information from free text as conveniently as accessing a database? One of the essential differences in free text is the lack of normalisation of concepts and relationships. This talk will show how the gap can be bridged using text mining based on Natural Language Processing.  The approach will be illustrated by showing how patients can be selected based on querying the free text in electronic health records e.g. cancer patients who are non-smokers over 65 years old.