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Posted to commits@ctakes.apache.org by ja...@apache.org on 2012/08/17 17:09:40 UTC
svn commit: r1374307 - /incubator/ctakes/site/trunk/content/ctakes/index.mdtext

Author: james-masanz
Date: Fri Aug 17 15:09:40 2012
New Revision: 1374307

URL: http://svn.apache.org/viewvc?rev=1374307&view=rev
Log:
update description of context for named entities to match what is found by assertion module as of cTAKES 2.0

Modified:
    incubator/ctakes/site/trunk/content/ctakes/index.mdtext

Modified: incubator/ctakes/site/trunk/content/ctakes/index.mdtext
URL: http://svn.apache.org/viewvc/incubator/ctakes/site/trunk/content/ctakes/index.mdtext?rev=1374307&r1=1374306&r2=1374307&view=diff
==============================================================================
--- incubator/ctakes/site/trunk/content/ctakes/index.mdtext (original)
+++ incubator/ctakes/site/trunk/content/ctakes/index.mdtext Fri Aug 17 15:09:40 2012
@@ -17,7 +17,7 @@ Notice:    Licensed to the Apache Softwa
            under the License.
 
 # Welcome to Apache cTAKES.
-Apache cTAKES: clinical Text Analysis and Knowledge Extraction System is an open-source natural language processing system for information extraction from electronic medical record clinical free-text. It processes clinical notes, identifying types of clinical named entitiesâââdrugs, diseases/disorders, signs/symptoms, anatomical sites and procedures. Each named entity has attributes for the text span, the ontology mapping code, context (family history of, current, unrelated to patient), and negated/not negated.
+Apache cTAKES: clinical Text Analysis and Knowledge Extraction System is an open-source natural language processing system for information extraction from electronic medical record clinical free-text. It processes clinical notes, identifying types of clinical named entities - medications, diseases/disorders, signs/symptoms, anatomical sites and procedures. Each named entity has attributes for the text span, the ontology mapping code, subject (patient, family member, etc.) and context (negated/not negated, conditional, generic).
 
 Apache cTAKES was built using the UIMA Unstructured Information Management Architecture framework and OpenNLP natural language processing toolkit. Its components are specifically trained for the clinical domain, and create rich linguistic and semantic annotations that can be utilized by clinical decision support systems and clinical research.
 
@@ -25,7 +25,7 @@ These components include:
  
   - Sentence boundary detection (OpenNLP technology)
   - Tokenization (rule-based)
-  - Morphologic normalization (NLMâs LVG)
+  - Morphologic normalization (NLM's LVG)
   - POS tagging (OpenNLP technology)
   - Shallow parsing (OpenNLP technology)
   - Named Entity Recognition