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From chen...@apache.org
Subject svn commit: r1417221 - /incubator/ctakes/site/trunk/content/ctakes/index.mdtext
Date Tue, 04 Dec 2012 22:12:33 GMT
Author: chenpei
Date: Tue Dec  4 22:12:32 2012
New Revision: 1417221

URL: http://svn.apache.org/viewvc?rev=1417221&view=rev
CMS commit to ctakes by chenpei


Modified: incubator/ctakes/site/trunk/content/ctakes/index.mdtext
URL: http://svn.apache.org/viewvc/incubator/ctakes/site/trunk/content/ctakes/index.mdtext?rev=1417221&r1=1417220&r2=1417221&view=diff
--- incubator/ctakes/site/trunk/content/ctakes/index.mdtext (original)
+++ incubator/ctakes/site/trunk/content/ctakes/index.mdtext Tue Dec  4 22:12:32 2012
@@ -16,12 +16,12 @@ Notice:    Licensed to the Apache Softwa
            specific language governing permissions and limitations
            under the License.
-# Welcome to Apache cTAKES (incubating).
+# Welcome to Apache cTAKES (incubating)
 Apache clinical Text Analysis and Knowledge Extraction System (cTAKES) 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
from various dictionaries including the Unified Medical Language System ([UMLS](http://www.nlm.nih.gov/research/umls/))
- 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, degree of certainty).
Some of the attributes are expressed as relations, for example the location of a clinical
condition (locationOf relation) or the severity of a clinical condition (degreeOf relation).

 Apache cTAKES was built using the Apache UIMA Unstructured Information Management Architecture
engineering framework and Apache OpenNLP natural language processing toolkit. Its components
are specifically trained for the clinical domain out of diverse manually annotated datasets,
and create rich linguistic and semantic annotations that can be utilized by clinical decision
support systems and clinical research. cTAKES has been used in a variety of use cases in the
domain of biomedicine such as phenotype discovery, translational science, pharmacogenomics
and pharmacogenetics.
-Apache cTAKES employs a number of rule-based and machine learning methods. Apache cTAKES
employs a number of rule-based and machine learning methods. Apache cTAKES [components](components.html)
+Apache cTAKES employs a number of rule-based and machine learning methods. Apache cTAKES
[components](components.html) include:
    1. Sentence boundary detection
    1. Tokenization (rule-based)

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