svn commit: r1417004 - /incubator/ctakes/site/trunk/content/ctakes/components.mdtext

[ch...@apache.org]

Author: chenpei
Date: Tue Dec  4 15:54:20 2012
New Revision: 1417004

URL: http://svn.apache.org/viewvc?rev=1417004&view=rev
Log:
Adding details about components

Added:
    incubator/ctakes/site/trunk/content/ctakes/components.mdtext   (with props)

Added: incubator/ctakes/site/trunk/content/ctakes/components.mdtext
URL: http://svn.apache.org/viewvc/incubator/ctakes/site/trunk/content/ctakes/components.mdtext?rev=1417004&view=auto
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--- incubator/ctakes/site/trunk/content/ctakes/components.mdtext (added)
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+Title: Apache cTAKES components
+Notice:    Licensed to the Apache Software Foundation (ASF) under one
+           or more contributor license agreements.  See the NOTICE file
+           distributed with this work for additional information
+           regarding copyright ownership.  The ASF licenses this file
+           to you under the Apache License, Version 2.0 (the
+           "License"); you may not use this file except in compliance
+           with the License.  You may obtain a copy of the License at
+           .
+             http://www.apache.org/licenses/LICENSE-2.0
+           .
+           Unless required by applicable law or agreed to in writing,
+           software distributed under the License is distributed on an
+           "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+           KIND, either express or implied.  See the License for the
+           specific language governing permissions and limitations
+           under the License.
+
+# Apache cTAKES Components
+
+### Sentence boundary detection 
+Apache OpenNLP technology with a model trained on manually annotated clinical data
+(see Savova et al, 2010)
+
+### Tokenization
+(rule-based) (see Savova et al, 2010)
+
+### Morphologic normalization (National Library of Medicine's Lexical Variant Generation tool
+http://www.nlm.nih.gov/research/umls/new_users/online_learning/LEX_004.htm
+
+### POS tagging 
+Apache OpenNLP technology with a model trained on manually annotated clinical data) (see Savova et al, 2010; upcoming 2013 publication
+
+### Shallow parsing 
+(Apache OpenNLP technology with a model trained on manually annotated clinical data) (see Savova et al, 2010)
+
+### Named Entity Recognition (see Savova et al, 2010)
+   - Dictionary mapping (lookup algorithm)
+   - Semantic typing is based on these UMLS semantic types: diseases/disorders, signs/symptoms, anatomical sites, procedures, medications
+
+### Assertion module
+Discovers negation, degree of certainty and the subject/experiencer of the clinical event (upcoming 2013 publication)
+
+### Dependency parser 
+Detects dependency relations between words (machine learning with a model trained on manually annotated clinical data) (see Choi and Palmer, 2011a; Choi and Palmer, 2011b; upcoming 2013 publication)
+
+### Constituency parser
+Apache OpenNLP technology with a model trained on manually annotated clinical data (see Zheng et al, 2011)
+
+### Semantic Role Labeler
+Assigns the predicate-argument structure of the sentence (who did what to whom when and where) (see Choi and Palmer, 2011a; Choi and Palmer, 2011b; upcoming 2013 publication)
+
+### Co-reference resolver
+Resolves co-referring entities. (machine learning with a model trained on manually annotated clinical data) (see Zheng et al, 2011)
+
+### Relation extractor
+discovers such attributes as the location and the severity of a clinical condition (machine learning with a model trained on manually annotated clinical data) (upcoming 2013 publication)
+
+### Drug Profile module
+discovers drug-specific attributes such as dosage, duration, form, frequency, route, strength (see Sohn et al, 2010; Savova et al, 2011)
+
+### Smoking status classifier
+past smoker, current smoker, non-smoker, smoker, unknown (see Savova et al, 2008)
+
+# Select Publications:
+Choi J, Palmer M. Getting the most out of Transition-based Dependency Parsing. 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies,. Portland, OR.: ACL-HLT 2011a , 2011.
+
+Choi J, Palmer M. Transition-based Semantic Role Labeling Using Predicate Argument Clustering. RELMS 2011: Relational Models of Semantics, held in conjunction with ACL-HLT 2011. Portland, OR, 2011b.
+
+Savova G, Olson J, Murphy S, Cafourek V, Couch F, Goetz M, Ingle J, Suman V, Chute C and Weinshilboum R. 2011. The electronic medical record and drug response research: automated discovery of drug treatment patterns for endocrine therapy of breast cancer. Journal of American Medical Informatics Association.
+
+Savova GK, Masanz JJ, Ogren PV, Zheng J, Sohn S, Kipper-Schuler KC, and Chute CG. Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applications. Journal of the American Medical Informatics Association : JAMIA 2010;17(5):507-13.
+
+Savova G, Ogren P, Duffy P, Buntrock J and Chute C. 2008. Mayo Clinic System for patient smoking status classification. J Am Med Inform Assoc. 2008; 15(1):25-8. PMID: 17947622
+
+Sohn S, Murphy SP, Masanz JJ, Kocher JP, Savova GK. Classification of medication status change in clinical narratives. AMIA Annual Symposium proceedings / AMIA Symposium. AMIA Symposium 2010;2010:762-6.
+
+Zheng J, Chapman W, Miller T, Lin C, Crowley R and Savova G. 2012. A system for coreference resolution for the clinical narrative. Journal of the American Medical Informatics Association. doi:10.1136/amiajnl-2011-000599

Propchange: incubator/ctakes/site/trunk/content/ctakes/components.mdtext
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