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Info

We recommend starting with the default properties and prebuilt train/test models.
The train and test models are anonymized feature sets (not text) generated by scrubber runtime.
scrubber.properties : all supported config options and features in one place.
Apache UIMA, Apache cTAKES, and WEKA distribution jars are loaded dynamically.


Default configuration

  • Developers can use Scrubber 3.X in "default mode" with the same settings as the provided train and test model files. Input and output settings are managed in scrubber.properties (file paths, database settings, method implementations).

Customize NLP pipeline

  • Scrubber uses Apache UIMA and Apache cTAKES packages, which together provide the NLP pipeline for lexical parsing and medical concept annotation. Generated feature sets are exported to the SQL database or model file (CSV, ARFF). The UIMA and cTAKES services used by Scrubber are defined and configured using scrubber.properties.

Customize Classifier

  • Scrubber can use different classifier implementations without recompiling the software.
  • By default scrubber dynamically loads the popular WEKA C4.5 decision tree classifier with multi-class support.


Software Features


Annotate text automatically

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