The CLAMP-Cancer System is a comprehensive clinical Natural Language Processing software that enables recognition and automatic encoding of clinical information in narrative patient reports. In addition to running a clinical concept extraction pipeline as well as an annotation pipeline, the individual components of the system can also be used as independent modules. The system lends itself for diverse applications in a broad range of clinical domains. The high performance language processing framework in CLAMP-Cancer consists of the following key building blocks:

NLP Pipelines

CLAMP-Cancer components builds on a set of high performance NLP components that were proven in several clinical NLP challenges such as i2b2 , ShARe/CLEF , and SemEVAL. A pipeline can be created and customized by a simple drag and drop on the individual CLAMP-Cancer components in the order that is desired. Upon creation of the pipeline, CLAMP-Cancer checks for errors in sequence and directs the user to the appropriate logical order with insertion of the required components for a working pipeline. The CLAMP-Cancer components are supported by knowledge resources consisting of medical abbreviations, dictionaries, section headers, and a corpus of 400 annotated clinical notes derived from MTsamples, a freely available resource of clinical narrative text. CLAMP-Cancer also provides built-in pipelines ready for use out of the box for a series of common clinical applications.

Machine learning and hybrid approaches

The CLAMP-Cancer framework provides alternative components for some tasks, utilizing rule based methods and/or machine learning methods such as support vector machines, and conditional random fields. These components can be customized by re-training on an annotated corpus, or editing the rule sets within the CLAMP-Cancer GUI to achieve a custom NLP task. The CLAMP-Cancer GUI version also provides built-in functionality to test the model, using the annotated corpora or n-fold cross validation.

Corpus management and annotation tool:

The user interface also provides required tools to maintain and annotate text corpora. It hosts an improved version of the brat annotation tool (reference?) for textual annotations.