This is the home of the Related Project - NLP cTAKES Project space.
News: cTAKES is now incubating as an a Top Level project on Apache Software Foundation Project!
There is a wealth of information within the plain text clinical narrative. The purpose of this cell is to harness the unstructured information by allowing i2b2 users to query and join that information with existing i2b2 concepts. Currently, the entire note is commonly stored as a single row in the observation_blob field in the observation_fact table in i2b2. One of NLP cTAKES' features is its capability to 'read' through and extract concepts from plain text notes and transform them into structured and normalized information. The purpose of this cell is to incorporate cTAKES and i2b2 by formatting the output of cTAKES into the i2b2 observation_fact table format (facts, concepts, modifiers, and values) which can then be easily queried by existing i2b2 interfaces.
There will be 2 main components: