  Extraction of concepts present in patient clinical records is an essential
step in clinical research. The 2010 i2b2/VA Workshop on Natural Language
Processing Challenges for clinical records presented concept extraction (CE)
task, with aim to identify concepts (such as treatments, tests, problems) and
classify them into predefined categories. State-of-the-art CE approaches
heavily rely on hand crafted features and domain specific resources which are
hard to collect and tune. For this reason, this paper employs bidirectional
LSTM with CRF decoding initialized with general purpose off-the-shelf word
embeddings for CE. The experimental results achieved on 2010 i2b2/VA reference
standard corpora using bidirectional LSTM CRF ranks closely with top ranked
systems.
