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1. Open a command prompt and change to the cTAKES_HOME directory.
Linux:
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2. Start the CAS Visual Debugger by running this command:
Linux:
The application may take a minute to start on slower hardware. |
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3. An analysis engine (AE) needs to be loaded in order to process text.
Click Open.
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4. Copy the text in the example at the right (next cell) and paste the
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3. From the menu bar, click Run -> Run AggregatePlaintextProcessor. |
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4. Named entities are now recognized in this clinical document.
or
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Collection processing engine (CPE)
Step | Example | |||||||||||||||
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1. Open a command prompt and change to the cTAKES_HOME directory:
Linux:
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2. Start the collection processing engine by running this command:
Linux:
The application may take a minute to start on slower hardware. |
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3. This will bring up the Collection Processing Engine Configurator. In the Menu bar click File >Open CPE Descriptor |
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4. Navigate to the file
Click Open. |
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5. Click the Play button (green/blue play arrow near the bottom). |
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6. You should see that one document was processed. You did process a collection of documents. In this case the collection only contained one just to show how to do it. Close the results window. |
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7. Close the CPE application. You may be prompted to save changes. Since this was just a test you may click the No button. |
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8. Open a new command prompt and change to the <cTAKES_HOME> |
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9. To test the results there is a comparison tool that will help show that the results match expectations with the following syntax:
Where: <First File> is the first file to compare; <Second File> is the second file to compare; <diff-html> is where the results are written to | Windows:
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10. The resulting file will open for you. Look at the comparison to see the annotations resulting from this pipeline.
Linux:
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Annotator | Description | Abbreviated | Example Analysis Engine (AE) | Example Collection processing Engine (CPE) | Example test data |
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Clinical Document Pipeline | the complete cTAKES pipeline to obtain majority of cTAKES annotations | cdp | cTAKES_HOME/cTAKESdesc/cdpdescdesc/ctakes-clinical-pipeline/desc/analysis_engine/AggregatePlaintextProcessor.xml | cTAKES_HOME/cTAKESdesc/cdpdesc/desc/ctakes-clinical-pipeline/desc/collection_processing_engine/test_plaintext.xml | cTAKES_HOME/testdata/cdptest |
Chunker | obtain cTAKES chunking annotations | chunker | cTAKES_HOME/cTAKESdescdesc/chunkerdesc/analysis_enginectakes-chunker/desc/ChunkerAggregate.xml | cTAKES_HOME/cTAKESdescdesc/chunkerdesc/collection_processing_enginectakes-chunker/desc/ChunkerCPE.xml | cTAKES_HOME/testdata/chunkertest |
Dependency Parser | obtain dependency parsing tree | dp | cTAKES_HOME/cTAKESdesc/dpdesc/desc/ctakes-dependency-parser/desc/analysis_engine/ClearParserTokenizedInfPosAggregateClearParserSRLTokenizedInfPosAggregate.xml | cTAKES_HOME/cTAKESdesc/dpdesc/desc/ctakes-dependency-parser/desc/collection_processing_engine/ClearParserCPEClearParserTestCPE.xml | cTAKES_HOME/testdata/dptest |
Drug NER | the annotator to obtain drug annotations | drugner | cTAKES_HOME/cTAKESdesc/drugnerdesc/desc/ctakes-drug-ner/desc/analysis_engine/DrugAggregatePlaintextProcesor.xml | cTAKES_HOME/cTAKESdesc/drugnerdescdesc/ctakes-drug-ner/desc/collection_processing_engine/DrugNER_PlainText_CPE.xml | cTAKES_HOME/testdata/drugnertest |
Dictionary Lookup | mapping cTAKES annotations to dictionaries (e.g., SNOMED_CT or RxNorm | lookup | cTAKES_HOME/cTAKESdesc/lookupdesc/desc/ctakes-dictionary-lookup/desc/analysis_engine/TestAggregateTAE.xml | cTAKES_HOME/cTAKESdesc/lookupdesc/desc/ctakes-dictionary-lookup/desc/collection_processing_engine/LookupCPE.xml | cTAKES_HOME/testdata/lookuptest |
PAD Term Spotter | identifying terms related to PAD | pad | cTAKES_HOME/cTAKESdesc/paddescdesc/ctakes-pad-term-spotter/desc/analysis_engine/Radiology_TermSpotterAnnotatorTAE.xml | cTAKES_HOME/cTAKESdesc/paddesc/desc/ctakes-pad-term-spotter/desc/collection_processing_engine/Radiology_Sample.xml | cTAKES_HOME/testdata/padtest |
Smoking Status | the annotator to obtain document or patient-level smoking status | smoking | cTAKES_HOME/cTAKESdesc/smokingdesc/desc/ctakes-smoking-status/desc/analysis_engine/SimulatedProdSmokingTAE.xml | cTAKES_HOME/cTAKESdesc/smokingdesc/desc/ctakes-smoking-status/desc/collection_processing_engine/Sample_SmokingStatus_output_flatfile.xml | cTAKES_HOME/testdata/smokingtest |
Side Effect | the annotator to find side effect mentions and sentences from clinical documents | sideeffect | cTAKES_HOME/cTAKESdesc/sideeffectdesc/desc/ctakes-side-effect/desc/analysis_engine/SideEffectAggregateTAE.xml | cTAKES_HOME/cTAKESdesc/sideeffectdesc/collection_processing_engine/desc/ctakes-side-effect/desc/cpe/SideEffectCPE.xml | cTAKES_HOME/testdata/sideeffecttest |
Next Steps
The cTAKES 3.1 Component Use Guide will help you to understand in great detail each of the cTAKES components that have been installed. In some cases you can learn how to improve the components. However, before you go on to process text in production you will need to consider dictionaries and models.
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- Dictionary Lookup: <cTAKES_HOME>/cTAKESdesc/lookupdescdesc/ctakes-dictionary-lookup/desc/analysis_engine/DictionaryLookupAnnotatorUMLS.xml
- (optional) Drug NER: <cTAKES_HOME>/cTAKESdesc/drugnerdesc/desc/ctakes-drug-ner/desc/analysis_engine/DictionaryLookupAnnotatorUMLS.xml
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- Download either the full version or the lite version from NIH Lexical Tools
- Extract the TGZ file that you downloaded with a tool like 7-zip (available online) to a temporary directory. On some operating systems, like Windows, this may need to be done in two steps, 1) to uncompress and 2) to unzip.
- Replace the directory <cTAKES_HOME>/resources/org/apache/lvgresourcesctakes/lvg/data/HSqlDb with data/HSqlDb from your extracted download. Replacing the entire directory is appropriate.
- In the future, you can upgrade to later versions of LVG of LVG by editing the <cTAKES_HOME>/resources/org/lvgresourcesapache/ctakes/lvg/data/config/lvg.properties file, replacing "lvg2008" with the name of the new release.
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Some models included in cTAKES may not represent your data distribution well. If you want to build or train your own models, please read the cTAKES 3.1 Component Use Guide, particularly:
- Training a sentence detector model
- Training a Part of Speech (POS) tagger model (Building a model Obtaining training data)
- Creating a Part of Speech (POS) tag dictionary (Building a tag dictionary)
- Training a chunker model (Building a model - Prepare GENIA training data)
- Training a dependency parser (Dependency Parser)