1. cTAKES
The clinical Text Analysis and
Knowledge Extraction System

2. cTAKES Overview Open source software Natural Language Processing (NLP)
Developed at Mayo Clinic
Contributed to the Open Health Natural Language Processing (OHNLP) Consortium
Built on the Apache UIMA framework
Unstructured Information Management Architecture
UIMA framework itself is also open source

3. Open Health Natural Language Processing (OHNLP) Consortium
Goal: Foster an open-source collaborative community around clinical NLP that can deliver best-of-breed annotators, leverage the dynamic features of UIMA flow- control, and establish the infrastructure for clinical NLP.

4. www.ohnlp.org Gateway to News Documentation Downloads
Forums for asking questions
Bug tracker for reporting issues
List of publications

5. cTAKES Goals Phenotype extraction
Generic – to be used for a variety of retrievals and use cases
Expandable – at the information model level and methods
Modular
Cutting edge technologies – best methods combining existing practices and novel research with rapid technology transfer
Best software practices (80M+ notes)
Commitment to both R and D in R&D

6. Original cTAKES Components
Sentence boundary detection (OpenNLP technology)
Tokenization (rule-based)
Morphologic normalization (NLM’s LVG)
POS tagging (OpenNLP technology)
Shallow parsing (OpenNLP technology)
Named Entity Recognition
Dictionary mapping (lookup algorithm)
Negation and context identification (both based on NegEx)

7. Original cTAKES Named Entities
Drug mentions
Disease/disorder mentions
Sign/symptom mentions
Anatomical site mentions
With these attributes
RxNorm code or Concept Unique Identifier (CUI) and SNOMED-CT codes.
Negation (denies chest pain)
Status (history of, family history of, possible/probable)

8. Additional cTAKES Components
Smoking status classifier
More detailed drug mention annotator
dosage
route
form
drug change status
and more
Peripheral Artery Disease (PAD) annotator
Dependency parser

9. Output Example: Disorder Object
“No evidence of unstable angina.”
Text: unstable angina
Associated codes:
SNOMED
UMLS CUI C
Named entity type: disease/disorder
Negation: true

10. cTAKES Configuration Options
XML configuration files
Control many things, such as
Dictionary location
Dictionary format
Which dictionaries to use
Type of input (plain text or CDA)
Forums contain details on creating your own dictionary

11. cTAKES Methods
Mayo clinical Text Analysis and Knowledge Extraction System (cTAKES): architecture, component evaluation and applications
Guergana K Savova, James J Masanz, Philip V Ogren, Jiaping Zheng, Sunghwan Sohn, Karin C Kipper-Schuler, Christopher G Chute.
JAMIA 2010;17:

12. References