Why CLAMP


Clinical Language Annotation, Modeling, and Processing Toolkit

High-performance NLP components

  • CLAMP components are built on proven methods in many clinical NLP challenges.
  • Includes I2B2 clinical NER (2009/2010-#2), SHARE/CLEF (2013-#1), SemEval2014 UMLS encoding (#1).

Machine learning and hybrid approaches

  • Train your own model for the machine learning based on components of CLAMP.
  • Evaluate custom models using a custom corpus.

Annotation and corpora management

  • Import clinical text corpora into the CLAMP workspace.
  • Annotate files using the built-in annotation tool that can be utilized in CLAMP projects, both as training and test datasets.

Customized pipelines

  • Build your own NLP pipelines from CLAMP.
  • Offer all the requisite components: named entity recognition, assertion, UMLS encoder, component customizations...

Knowledge sources and sample clinical text

  • Provide all the knowledge resources required for CLAMP components.
  • Dictionaries, section header list, medical abbreviation list...

Interoperability and Scalability

  • Build on the UIMA framework.
  • Compatible with other systems such as cTAKES.
  • Utilize the cTAKES’ type system for lower linguistic level annotations.

Tutorial


CLAMP manual...

CLAMP Demo for Smoking Status

CLAMP NLP

CLAMP Demo for Lab Test

CLAMP Lab Test NLP

CLAMP Dictionary Lookup Tutorial

CLAMP NLP

NER Model Development

CLAMP NER NLP Machine Learning

CLAMP Demo for Labtest

CLAMP Lab Test NLP

CLAMP Corpus Annotation

CLAMP Corpus NLP Annotation Machine Learning

CLAMP Basic Pipeline Demo

CLAMP Pipeline NLP

CLAMP NER Attribute Pipeline demo

CLAMP Pipeline NER NLP

Clients


World’s most dynamic healthcare institutions are using CLAMP