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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.
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.
CLAMP Demo for Smoking Status
CLAMP Demo for Lab Test
CLAMP Dictionary Lookup Tutorial
NER Model Development
CLAMP Demo for Labtest
CLAMP Corpus Annotation
CLAMP Basic Pipeline Demo
CLAMP NER Attribute Pipeline demo
World’s most dynamic healthcare institutions are using CLAMP