The CLAMP-Cancer annotation module enables you to annotate customized entities and specify relations between them in your desired corpus . These annotations enable you to assign additional clinical information to a selected text and develop an annotated corpus that’s more suitable to the specific task that you have. Task-specific models can be developed and used in the machine-learning modules of CLAMP-Cancer or any other system of your choice. Before using this function, you need to:
After completing these steps, you will be able to annotate the imported files based on some predefined structure. The following steps will guide you on how to perform the steps mentioned above.
A new project with the name that you have specified is created and placed in the Corpus panel.
Double click the project name to view its content. The created project contains two main
folders:
Corpus: Contains the files that will be annotated
Models: Contains the machine learning models generated
from the annotated files.In
addition, the prediction results generated from
the n-fold cross-validation process and gold
standard annotations are included in this folder.