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These instructions are under construction.
These instructions are for end users. With these instructions you can install cTAKES, configure it, and use it to process text (typically text associated with a medical record). If you were planning to expand, change, or modify the code within cTAKES, refer to the cTAKES 3.0 Developer Guide.
These instructions will cover installation and a test of the main product including trained models for sentence detection and tagging parts of speech, dictionaries from a subset of the UMLS, a very small subset of the full LVG resource, etc. Optional components will also be described.
Once you have finished installation of cTAKES, you will be able to see what cTAKES is capable of. Further exploitation of the software's ability may require following a few additional steps involving what dictionaries are being used. These are the last steps in these instructions.
Prerequisites
Step |
Example |
|---|---|
1. Make sure you have Java 1.6 or higher. Most systems come with Java already installed. java -version |
Windows: C:\>java -version java version "1.6.0_20" Java(TM) SE Runtime Environment (build 1.6.0_20-b02) Java HotSpot(TM) Client VM (build 16.3-b01, mixed mode, sharing) tbleeker@system:/$ java -version java version "1.6.0_22" OpenJDK Runtime Environment (IcedTea6 1.10.1) (6b22-1.10.1-0ubuntu1) OpenJDK 64-Bit Server VM (build 20.0-b11, mixed mode) |
Install cTAKES
Step |
Example |
|---|---|
1. Navigate to the downloads page for a released version on Apache |
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2. Download the cTAKES-3.0.zip file. |
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3. c:\cTAKES-3.0 Linux: /usr/bin/cTAKES-3.0 This folder we will call <cTAKES_HOME>. You will need to refer to the directory later. |
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Process documents using cTAKES
This version allows you to test most components bundled in cTAKES in two different ways:
- Using cTAKES CAS Visual Debugger (CVD) to view the results stored as XCAS files or run the annotators or
- Using cTAKES collection processing engine (CPE) to process documents in cTAKES_HOME/testdata directory
CAS Visual Debugger (CVD)
Step |
Example |
|---|---|
1. Open a command prompt and change to the cTAKES_HOME directory. cd \cTAKES-3.0 Linux: cd /usr/bin/cTAKES-3.0 |
Note cTAKES_HOME must be your current directory unless you are skilled at setting paths on your machine. |
2. Start the CAS Visual Debugger by running this command: bin\runctakesCVD.bat Linux: bin/runctakesCVD.sh 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. <cTAKES_HOME>/ctakes-clinical-pipeline/desc/analysis_engine/AggregatePlaintextProcessor.xml Click Open.
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4. Copy the example text from the next cell in this table and paste the contents into the Text section of CVD, replacing the text that is already there. <cTAKES_HOME>/testdata/cdptest/testinput/plaintext/testpatient_plaintext_1.txt |
Dr. Nutritious |
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 |
|---|---|
1. Open a command prompt and change to the cTAKES_HOME directory: cd C:\cTAKES3.0 Linux: cd /usr/bin/cTAKES3.0 |
Note Note that cTAKES_HOME must be your current directory unless you are skilled at setting paths on your machine. |
2. Start the collection processing engine by running this command: bin\runctakesCPE.bat Linux: bin/runctakesCPE.sh 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 <cTAKES_HOME>/desc/ctakes-clinical-pipeline/desc/collection_processing_engine/test_plaintext.xml 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: java -cp ctakes-utils-3.0.0.jar org.apache.ctakes.utils.xcas_comparison.Compare <First File> <Second File> <diff-html> 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: java -cp ctakes-utils-3.0.0.jar org.apache.ctakes.utils.xcas_comparison.Compare ^ "testdata\cdptest\testoutput\plaintext\sample_note_plaintext.xml" ^ "testdata\cdptest\testsampleoutput\plaintext\sample_note_plaintext.xml" ^ c:\stuff\diff-html.html java -cp ctakes-utils-3.0.0.jar org.apache.ctakes.utils.xcas_comparison.Compare \ "/usr/bin/cTAKES3.0/testdata/cdptest/testoutput/plaintext\sample_note_plaintext.xml" \ "/usr/bin/cTAKES3.0/testdata/cdptest/testsampleoutput/plaintext/sample_note_plaintext.xml" \ /tmp/diff-html.html |
10. The resulting file will open for you. Look at the comparison to see the annotations resulting from this pipeline. c:\stuff\diff-html.html Linux: /tmp/diff-html.html |
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Using the same CVD and CPE programs in the manner described above, you can test all the other components. The analysis engines and collection processing engines shipped with cTAKES for some of the annotators are described in the following table.
Annotator |
Description |
Abbreviated |
Example Analysis Engine (AE) |
Example Collection processing Engine (CPE) |
Example test data |
|---|---|---|---|---|---|
Clinical Document Pipeline |
the complete cTAKES pipeline to obtain majority of cTAKES annotations |
cdp |
cTAKES_HOME/desc/ctakes-clinical-pipeline/desc/analysis_engine/AggregatePlaintextProcessor.xml |
cTAKES_HOME/desc/ctakes-clinical-pipeline/desc/collection_processing_engine/test_plaintext.xml |
cTAKES_HOME/testdata/cdptest |
Chunker |
obtain cTAKES chunking annotations |
chunker |
cTAKES_HOME/desc/ctakes-chunker/desc/ChunkerAggregate.xml |
cTAKES_HOME/desc/ctakes-chunker/desc/ChunkerCPE.xml |
cTAKES_HOME/testdata/chunkertest |
Dependency Parser |
obtain dependency parsing tree |
dp |
cTAKES_HOME/desc/ctakes-dependency-parser/desc/analysis_engine/ClearParserSRLTokenizedInfPosAggregate.xml |
cTAKES_HOME/desc/ctakes-dependency-parser/desc/collection_processing_engine/ClearParserTestCPE.xml |
cTAKES_HOME/testdata/dptest |
Drug NER |
the annotator to obtain drug annotations |
drugner |
cTAKES_HOME/desc/ctakes-drug-ner/desc/analysis_engine/DrugAggregatePlaintextProcesor.xml |
cTAKES_HOME/desc/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/desc/ctakes-dictionary-lookup/desc/analysis_engine/TestAggregateTAE.xml |
cTAKES_HOME/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/desc/ctakes-pad-term-spotter/desc/analysis_engine/Radiology_TermSpotterAnnotatorTAE.xml |
cTAKES_HOME/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/desc/ctakes-smoking-status/desc/analysis_engine/SimulatedProdSmokingTAE.xml |
cTAKES_HOME/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/desc/ctakes-side-effect/desc/analysis_engine/SideEffectAggregateTAE.xml |
cTAKES_HOME/desc/ctakes-side-effect/desc/collection_processing_engine/SideEffectCPE.xml |
cTAKES_HOME/testdata/sideeffecttest |
Next Steps
The cTAKES 3.0 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.
Dictionaries
Bundled UMLS Dictionaries
cTAKES includes the complete UMLS (SNOMED-CT and RxNorm) dictionaries.
- An rxnorm_index database (a Lucene index) containing drug names from RxNorm
- A UMLS database (using two hsqldb tables) containing anatomical sites, procedures, signs/symptoms, and disorders/diseases from SNOMED-CT (umls_ms_2011ab)
To use them, you must have a UMLS username and password, and an Internet connection.
Note
If you do not have a UMLS username and password, you may request one at UMLS Terminology Services
In order to use the UMLS dictionaries shipped with cTAKES you will need to do two things:
(1) Change the UMLSUser and UMLSPW <nameValuePair> strings in these descriptor files with your UMLS username and password.
- Dictionary Lookup: <cTAKES_HOME>/desc/ctakes-dictionary-lookup/desc/analysis_engine/DictionaryLookupAnnotatorUMLS.xml
- (optional) Drug NER: <cTAKES_HOME>/desc/ctakes-drug-ner/desc/analysis_engine/DictionaryLookupAnnotatorUMLS.xml
The following shows where in the files you would make the changes. (Do not change the <configurationParameters> by the same name.)
<nameValuePair> <name>UMLSUser</name> <value> <string>YOUR_UMLS_USERNAME_HERE</string> </value> </nameValuePair> <nameValuePair> <name>UMLSPW</name> <value> <string>YOUR_UMLS_PASSWORD_HERE</string> </value> </nameValuePair>
(2) Include the DictionaryLookupAnnotatorUMLS.xml Analysis Engine within your aggregate Analysis Engine or switch to the ones provided by cTAKES. cTAKES has provided duplicates of shipped Analysis Engine descriptors, put UMLS in the name, and placed DictionaryLookupAnnotatorUMLS.xml within them for these components:
- Dictionary Lookup
- Clinical Documents pipeline
- Drug NER
- Side Effect
So you simply need to switch to using those descriptors. For example, if you were using AggregateCdaProcessor.xml in the Clinical Documents pipeline you would switch to using AggregateCdaUMLSProcessor.xml instead and you will now hook into the complete dictionaries.
You can, of course, modify your own aggregate Analysis Engine files and place the DictionaryLookupAnnotatorUMLS.xml Analysis Engine within them.
Since this is an in-memory database implementation, please be patient during the initial load as it could take approximately 20-30 seconds for the database to initialize.
If you would like to go back to using the small sample dictionaries that do not require a UMLS username, use the DictionaryLookupAnnotator.xml (UMLS is not in the file name) Analyis Engine descriptor in your aggregate. Just removing your password from the DictionaryLookupAnnotatorUMLS.xml files will not switch you back to the small sample dictionaries.
LVG
We have successfully tested the 2008 release of the full LVG data. In order to use this release of the full LVG data you should:
- 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/ctakes/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 by editing the <cTAKES_HOME>/resources/org/apache/ctakes/lvg/data/config/lvg.properties file, replacing "lvg2008" with the name of the new release.
Building Your Own Dictionaries
To install customized dictionaries for RxNorm, SNOMED-CT, or other vocabularies that are available through the UMLS, see the following posts on the cTAKES forums:
- https://cabig-kc.nci.nih.gov/Vocab/forums/viewtopic.php?f=28&t=423
- https://cabig-kc.nci.nih.gov/Vocab/forums/viewtopic.php?f=28&t=80&start=20#p1459
Models
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 3.0 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)