Roland is a PhD student in the natural language processing group at the University of Sheffield. He is focussing on relation extraction from biomedical literature in combination with the Unified Medical Language System (UMLS). Since October 2015 he is also working for the German Research Center for Artificial Intelligence (DFKI GmbH).
Detecting adverse-drug effects in natural language using limited training data
By Roland Roller on 29th October 2015
A large amount of information is provided in text documents but difficult to access for computer programs. In order to detect complex information it is often important to understand the relationships between words and entities in sentences. A relation can express for instance that a disease has a particular finding or a that a drug […]
Posted in Autumn 2015, Feature Article