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	CTAKES:Menu cTAKES 3.0 to IncludeCTAKES:
	Menu cTAKES 3.0 to Include

Warning

These instructions are under construction.

These instructions are for end users. With these instructions you can install Apache 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 Install 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 are described in the Component Use Guide.

Once you have finished installing cTAKES and its separately-bundled resources, 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. The last section on this page covers these next steps.

Prerequisites

Step

Example

1. Make sure you have Java 1.6 or higher. Most systems come with Java already installed.

Run this command to check your version.

Windows and Linux:

Code Block

language	none

java -version

Windows:

Code Block

language	none

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)

Linux:

Code Block

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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 cTAKES downloads page on the Apache site and download the binary package. Select a mirror site and press the Change button to modify the URL to your desired mirror location before doing the download or accept the default.

Windows:
Download the ZIP file.
Linux:
Take the link for the file you want and use wget Use wget to obtain the *.TAR.GZ file.
wget <URL of the file>file from downloads>

Noteinfo
The download time will be commensurate with 700MB ~165MB of data.
Warning
A release candidate is currently available at:http://people.apache.org/~chenpei/ctakes-3.0.0-incubating/rc5/target/

Windows:

Linux:

Code Block

language	none

HTTP request sent, awaiting response... 200 OK
Length: 763500777 (728M) [application/x-gzip]
Saving to: `apache-ctakes-3.0.0-incubating-bin.tar.gz'

13% [===========>                                     ] 106,548,331 1.13M/s eta 11m 9s

2. (Optional but recommended) Verify the downloaded files against a file signature to ensure you have the proper and complete file.

No example

3. Unzip the file you downloaded into a directory that you want to be the cTAKES install location. The compressed files contain a single directory at the top level. This folder we will call <cTAKES_HOME>. You will need to refer to this directory later.

Windows:

Code Block

language	none

C:\apache-ctakes-3.0.0-incubating

Linux:

Code Block

language	none

/usr/local/apache-ctakes-3.0.0-incubating

Windows:

Linux:

Code Block

language	none

tar -xvf apache-ctakes-3.0.0-incubating-bin.tar.gz -C /usr/local

Step

Example

4. Download UMLS and model resources...

Warning
The location of these resources is not prepared yet. Replace this box with instructions.

No example

Process documents using cTAKES

This version allows you to test most components bundled in cTAKES in two different ways:

Using the bundled UIMA CAS Visual Debugger (CVD) to view the results stored as XCAS files or run the annotators
Using the bundled UIMA Collection Processing Engine (CPE) to process documents in cTAKES_HOME/testdata directory

You will need a windowing environment on Linux to run these tools.

CAS Visual Debugger (CVD)

cd \apache-ctakes-3.0.0-incubating\bin

Windows:
Image Added

Linux:

cTAKES 3.0 Dictionaries and models. These resources are required to operate cTAKES.

Info
Due to licensing considerations and easy of installability, one download from an external location was established with all the resources you will need. Licensing for these resources is found within the download.

Info
Download time will be commensurate with 1GB of data.

Windows:
Go to cTAKES resources and download the ZIP file with a matching version from the ctakesresources project.
Unzip the files into a temporary location such as C:\temp.

Linux:
Obtain the URL of the version matching ZIP file from cTAKES resources, get the file, and unzip to a temporary location.

1. Open a command prompt and change to the cTAKES_HOME directory.
Windows:

Code Block

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languagelang	none

cd /usr/local/apache-ctakes-3.0.0-incubating/bin

Note

title	Note

Note that <cTAKES_HOME>/bin 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:
Windows:

Code Block

language	none

runctakesCVD.bat

Linux:

Code Block

language	none

runctakesCVD.sh

The application may take a minute to start on slower hardware.

No example

tmp
wget http://sourceforge.net/projects/ctakesresources/files/ctakes-resources-3.0.1.zip
sudo unzip ctakes-resources-3.0.1.zip

5. Copy (or move) the resources to cTAKES_HOME.
Copy the contents of the temporary resources directory (and all sub-directories) to <cTAKES_HOME>/resources.

Info
There may be conflicts while taking this action. Overwrite the cTAKES_HOME files with those in the resources download.

3. 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.
This example file can also be found in test data:

Code Block

language	none

<cTAKES_HOME>/testdata/cdptest/testinput/plaintext/testpatient_plaintext_1.txt

WarningThis file may not be in the binary distribution only src?

Windows:

Code Block

lang	none

Dr. Nutritious

Medical Nutrition Therapy for Hyperlipidemia
Referral from: Julie Tester, RD, LD, CNSD
Phone contact: (555) 555-1212
Height: 144 cm Current Weight: 45 kg Date of current weight: 02-29-2001
Admit Weight: 53 kg BMI: 18 kg/m2
Diet: General
Daily Calorie needs (kcals): 1500 calories, assessed as HB + 20% for activity.
Daily Protein needs: 40 grams, assessed as 1.0 g/kg.
Pt has been on a 3-day calorie count and has had an average intake of 1100 calories.
She was instructed to drink 2-3 cans of liquid supplement to help promote weight gain.
She agrees with the plan and has my number for further assessment. May want a Resting
Metabolic Rate as well. She takes an aspirin a day for knee pain.

4. An analysis engine (AE) needs to be loaded in order to process text.
Use the Run-> Load AE menu bar command. Navigate to the file

Code Block

language	none

<cTAKES_HOME>/desc/ctakes-clinical-pipeline/desc/analysis_engine/AggregatePlaintextProcessor.xml

Click Open.
Loading the analysis engine may take a minute. Once the analysis engine has successfully loaded you should see a tree in the Analysis Results frame:

Wiki Markup
CAS Index Repository \\ \* SofaIndex \[0\] \\ \* AnnotationIndex \[1\] \\

Image Removed

5. From the menu bar, click Run -> Run AggregatePlaintextProcessor.

Image Removed

6. You'll get a list of all the annotations for this clinical document in the Analysis Results frame. Annotations such as concepts mentioned, division by sentence, etc from the pipeline are viewable. To see one, in the Analysis Results frame, click on the key in front of:

CAS Index Repository
* AnnotationIndex
* uima.tcas.Annotation
* org.apache.ctakes.medfacts.types.Concept

This will show an AnnotationIndex in the lower frame. Select any annotation in that lower frame and you will see the text discovered in
the Text frame on the right like the concept of the problem Hyperlipidemia.
For a medication example select this

CAS Index Repository
* AnnotationIndex
* uima.tcas.Annotation
* org.apache.ctakes.typsystem.type.textsem.IdentifiedAnnotation
* org.apache.ctakes.typsystem.type.textsem.EventMention
* org.apache.ctakes.typsystem.type.textsem.MedicationEventMention

Now select items in the lower frame to see the text being annotated.
You may close the CAS Visual Debugger (CVD) application if you wish.

Image Removed

...

xcopy /s C:\temp\ctakes-resources-3.0.1\resources C:\apache-ctakes-3.0.0-incubating\resources

Linux:

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cp -R /tmp/resources/* /usr/local/apache-ctakes-3.0.0-incubating/resources

(Optional) Add UMLS access rights

Note

In the initial setup cTAKES will recognize only few sample concepts in text. If you wish to perform named entity recognition or concept identification for anything other than these few words, you will need to 1) obtain the rights to use UMLS resources 2) add those credentials to cTAKES, and 3) use an aggregate that makes use of those UMLS resources. If you don't, cTAKES will work but won't recognize much.

Step

Example

1. If you do not have a UMLS username and password, you may request one at UMLS Terminology Services.

No example

2. Edit the following files. Add the ctakes.umlsuser and ctakes.umlspw parameters to the java command found in the file.adding in your UMLS. Make sure you substitute your actual ID and password if you cut and paste the example.

Windows:

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<cTAKES_HOME>\bin\runctakesCVD.bat
<cTAKES_HOME>\bin\runctakesCPE.bat

Linux:

Code Block

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<cTAKES_HOME>/bin/runctakesCVD.sh
<cTAKES_HOME>/bin/runctakesCPE.sh

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java -Dctakes.umlsuser=<YOUR_UMLS_ID_HERE> -Dctakes.umlspw=<YOUR_UMLS_PASSSWORD_HERE> -cp ...

3. You will select an aggregate when you run cTAKES (continue reading).

No example

Process documents using cTAKES

This version allows you to test most components bundled in cTAKES in two different ways:

Using the bundled UIMA CAS Visual Debugger (CVD) to view the results stored as XCAS files or run the annotators
Using the bundled UIMA Collection Processing Engine (CPE) to process documents in cTAKES_HOME/testdata directory

You will need a windowing environment on Linux to run these tools.

CAS Visual Debugger (CVD)

Windows:

Step

Example

1. Open a command prompt and change to the cTAKES_HOME directory.

Note
It is best if <cTAKES_HOME> is your current directory. The scripts will change directories, so being home to

the cTAKES_HOME directory:

run the command is best.

Windows:

Code Block

language	none

cd \apache-ctakes-3.0.0-incubating\bin

Linux:

Code Block

language	none

cd /usr/local/apache-ctakes-3.0.0-incubating/bin

Note

title	Note

Note that <cTAKES_HOME>/bin 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: CAS Visual Debugger by running this command:
The application may take a minute to start on slower hardware.

Windows:

Code Block

language	none

runctakesCPEbin\runctakesCVD.bat

Linux:

Code Block

language	none

runctakesCPEbin/runctakesCVD.sh

The application may take a minute to start on slower hardware.

No example

3. This will bring up the Collection Processing Engine Configurator. In the Menu bar click File >Open CPE Descriptor

37

4. Navigate to the file

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<cTAKES_HOME>/desc/ctakes-clinical-pipeline/desc/collection_processing_engine/test_plaintext.xml

Click Open.

No example

5. Click the Play button (green/blue play arrow near the bottom).

38

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.

7. Close the CPE application. You may be prompted to save changes. Since this was just a test you may click the No button.

8. Open a new command prompt and change to the <cTAKES_HOME>

9. To test the results there is a comparison tool that will help show that the results match expectations with the following syntax:

Code Block

language	none

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
Copy and paste the example at the right (next cell) which has had our
example files already substituted into a command prompt to run. In this
case we have shipped an example of what the output should be for you to
compare against.

Code Block

language	none

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

Linux:

Code Block

language	none

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.
Windows:

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language	none

c:\stuff\diff-html.html

Linux:

Code Block

language	none

/tmp/diff-html.html

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

title	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.)

Code Block

language	none

<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:

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:

...

3. 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.

You can also download a copy of the file from here

Code Block

lang	none

Dr. Nutritious

Medical Nutrition Therapy for Hyperlipidemia
Referral from: Julie Tester, RD, LD, CNSD
Phone contact: (555) 555-1212
Height: 144 cm Current Weight: 45 kg Date of current weight: 02-29-2001
Admit Weight: 53 kg BMI: 18 kg/m2
Diet: General
Daily Calorie needs (kcals): 1500 calories, assessed as HB + 20% for activity.
Daily Protein needs: 40 grams, assessed as 1.0 g/kg.
Pt has been on a 3-day calorie count and has had an average intake of 1100 calories.
She was instructed to drink 2-3 cans of liquid supplement to help promote weight gain.
She agrees with the plan and has my number for further assessment. May want a Resting
Metabolic Rate as well. She takes an aspirin a day for knee pain.

4. An analysis engine (AE) needs to be loaded in order to process text.
If you installed the optional UMLS resources, use

No Format
AggregatePlaintextUMLSProcessor.xml

rather than

No Format
AggregatePlaintextProcessor.xml

in this step.
Use the Run-> Load AE menu bar command. Navigate to the file

Code Block

language	none

<cTAKES_HOME>
  /desc
    /ctakes-clinical-pipeline
      /desc
        /analysis_engine
          /AggregatePlaintextProcessor.xml

Click Open.
Loading the analysis engine may take a minute. Once the analysis engine has successfully loaded you should see a tree in the Analysis Results frame:

CAS Index Repository
* SofaIndex [0]
* AnnotationIndex [1]

Image Added

5. From the menu bar, click Run -> Run AggregatePlaintextProcessor or "Run AggregatePlaintextUMLSProcessor".

Image Added

6. You'll get a list of all the annotations for this clinical document in the Analysis Results frame. Annotations such as concepts mentioned, division by sentence, etc from the pipeline are viewable. To see one, in the Analysis Results frame, click on the key in front of:

CAS Index Repository
* AnnotationIndex
* uima.tcas.Annotation
* org.apache.ctakes.medfacts.types.Concept

This will show an AnnotationIndex in the lower frame. Select any annotation in that lower frame and you will see the text discovered in
the Text frame on the right like the concept of the problem Hyperlipidemia.

For a medication example select this

CAS Index Repository
* AnnotationIndex
* uima.tcas.Annotation
* org.apache.ctakes.typsystem.type.textsem.IdentifiedAnnotation
* org.apache.ctakes.typsystem.type.textsem.EventMention
* org.apache.ctakes.typsystem.type.textsem.MedicationEventMention

Now select items in the lower frame to see the text being annotated.

You may close the CAS Visual Debugger (CVD) application if you wish.

Image Added

Collection Processing Engine (CPE)

Step

Example

1. Open a command prompt and change to the cTAKES_HOME directory:

Note
It is best if <cTAKES_HOME> is your current directory. The scripts will change directories, so being home to run the command is best.

Windows:

Code Block

language	none

cd \apache-ctakes-3.0.0-incubating

Linux:

Code Block

language	none

cd /usr/local/apache-ctakes-3.0.0-incubating

2. Create a directory for some test data.

Windows:mkdir testdata

3. Download this sample file and place it into the testdata directory.

No example

4. Start the collection processing engine by running this command:
The application may take a minute to start on slower hardware.

Windows:

Code Block

language	none

bin\runctakesCPE.bat

Linux:

Code Block

language	none

bin/runctakesCPE.sh

5. This will bring up the Collection Processing Engine Configurator. In the Menu bar click File >Open CPE Descriptor

Image Added

6. Navigate to the following file, which uses the AggregateCdaProcessor

Code Block

lang	none


<cTAKES_HOME>
  /desc
    /ctakes-clinical-pipeline
      /desc
        /collection_processing_engine
          /test1.xml

Click Open.

No example

7. Change the Collection reader input directory to testdata, which contains a CDA file(s).
Within the CAS Consumers pane of the same window, change the output directory to testdata/output

Image Added

8. Click the Play button (green/blue play arrow near the bottom).

Info

What just happened? You placed a sample CDA document into the input of a pipeline. The pipeline was a file system reader that will process all files in a directory. The processing was accomplished by the chunker cTAKES component (noted by the name of the Analysis Engine pictured). One resulting file for each input file was placed into the output directory. This output file is an XML file that annotates the noun phrases and verb phrases.

Image Added

9. 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.

Note
This example of using the CPE GUI did not use the UMLS resources. If you wish to perform named entity recognition or concept identification for anything other than a few words, you will need to 1) obtain the rights to use UMLS resources 2) add those credentials to cTAKES, and 3) use an aggregate that makes use of those UMLS resources (see above).

Image Added

10. Close the CPE application. You may be prompted to save changes. Since this was just a test you may click the No button.

No example

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.

Warning
cTAKES 3.0 binary distributions did not include test data. Loading the CPE descriptors into the CPE tool will require resetting the input and output directories. Test files could be obtained from the cTAKES 2.5 release binary distribution. Look for a testdata directory in cTAKES_HOME.

Annotator	Description	Example Aggregate Analysis Engine (AE)	Example Collection processing Engine (CPE)
Clinical Document Pipeline	The complete cTAKES pipeline to obtain majority of cTAKES annotations	<cTAKES_HOME>/desc/ctakes-clinical-pipeline/desc/analysis_engine/AggregatePlaintextUMLSProcessor.xml	<cTAKES_HOME>/desc/ctakes-clinical-pipeline/desc/collection_processing_engine/test1.xml
Chunker	Obtain cTAKES chunk annotations	NA	NA
Dependency Parser	Obtain dependency parsing tree	<cTAKES_HOME>/desc/ctakes-dependency-parser/desc/analysis_engine/ClearParserSRLTokenizedInfPosAggregate.xml	<cTAKES_HOME>/desc/ctakes-dependency-parser/desc/collection_processing_engine/ClearParserTestCPE.xml
Drug NER	The annotator to obtain drug annotations	<cTAKES_HOME>/desc/ctakes-drug-ner/desc/analysis_engine/DrugAggregatePlaintextUMLSProcesor.xml	<cTAKES_HOME>/desc/ctakes-drug-ner/desc/collection_processing_engine/DrugNER_PlainText_CPE.xml
Dictionary Lookup	Mapping cTAKES annotations to dictionaries (e.g., SNOMED_CT or RxNorm	<cTAKES_HOME>/desc/ctakes-dictionary-lookup/desc/analysis_engine/TestAggregateTAE.xml	NA
PAD Term Spotter	Identifying terms related to 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
Relation Extractor	Annotate certain relations between certain Event, Entity, and Modifier annotations	<cTAKES_HOME>/desc/ctakes-relation-extractor/desc/analysis_engine/RelationExtractorAggregate.xml	N/A
Smoking Status	The annotator to obtain document or patient-level smoking status	<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
Side Effect	The annotator to find side effect mentions and sentences from clinical documents	<cTAKES_HOME>/desc/ctakes-side-effect/desc/analysis_engine/SideEffectAggregateTAE_UMLS.xml	<cTAKES_HOME>/desc/ctakes-side-effect/desc/collection_processing_engine/SideEffectCPE.xml

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.

Also, before you go on to process text in production, you will want to consider dictionaries and models. If you did not obtain the rights yet to the UMLS resources and models, you will want to do so. Be aware, the models (within the separate resources download) have been trained on data that may not match your data well enough to be effective. In some cases you might want to modify the dictionaries and train models using your own data.

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Key

Prerequisites

Install cTAKES

Process documents using cTAKES

CAS Visual Debugger (CVD)

(Optional) Add UMLS access rights

Process documents using cTAKES

CAS Visual Debugger (CVD)

Next Steps

Dictionaries

Bundled UMLS Dictionaries

LVG

Building Your Own Dictionaries

Models

Collection Processing Engine (CPE)

Next Steps