Unstructured information comprises a valuable source of data in clinical
records. For text mining in clinical records, concept extraction is the first
step in finding assertions and relationships. This study presents a system
developed for the annotation of medical concepts, including medical problems,
tests, and treatments, mentioned in clinical records. The system combines six
publicly available named entity recognition system into one framework, and uses
a simple voting scheme that allows to tune precision and recall of the system
to specific needs.