The biomedical literature is growing rapidly, and the extraction of meaningful information
from the large amount of literature is increasingly important. Biomedical named entity …

One effective way to improve the state of the art is through competitions. Following the
success of the Critical Assessment of protein Structure Prediction (CASP) in bioinformatics …

Named entity recognition (NER) is an important step in biomedical information extraction
pipelines. Tools for NER should be easy to use, cover multiple entity types, be highly …

Motivation: The scientific literature embeds an enormous amount of relational knowledge,
encompassing interactions between biomedical entities, like proteins, drugs, and symptoms …

Supplying a comprehensive overview of healthcare analytics research, Healthcare Data
Analytics provides an understanding of the analytical techniques currently available to solve …

Background Since their introduction in 2009, the BioNLP Shared Task events have been
instrumental in advancing the development of methods and resources for the automatic …

Motivation With the exponential growth of the life sciences literature, biomedical text mining
(BTM) has become an essential technology for accelerating the extraction of insights from …

Motivation: The hallmarks of cancer have become highly influential in cancer research. They
reduce the complexity of cancer into 10 principles (eg resisting cell death and sustaining …

Event extraction aims to identify an event and then extract the arguments participating in the
event. Despite the great success in sentencelevel event extraction, events are more …

We participate in the BioNLP 2013 Shared Task with Turku Event Extraction System (TEES)
version 2.1. TEES is a support vector machine (SVM) based text mining system for the …