Built-in pipelines

In order to facilitate a convenient utility of CLAMP-Cancer, a series of pipelines that could be directly adopted in common clinical applications are pre_built and displayed in PipelineLibrary. Users can directly drag one of them (e.g., smoking_status, ) from the PipelineLibrary and drop it under My Pipeline (see figures below). The required NLP components of these pipelines are already configured. CLAMP-Cancer allows you to customize each of these components to fit your needs.
First, you need to import your files; for more information go to "Import input files” section.

Depending on what your use case is, the current built-in pipelines are divided into the following categories:

1. General: automatically annotates concepts and their attribute for general use, including:
   CLAMP-Cancer-ner: annotates the disease, procedure and medication concepts
   CLAMP-Cancer-ner-attribute: annotates the attributes of disease (e.g., body location of a disease), lab procedure (e.g., value of a lab test ) and medication (e.g., dosage of a medication) concepts
   Disease-attribute: annotate the attributes of diseases, including body locations (e.g., left atrium), severity degrees (e.g., mild, severe) and uncertainty (e.g., probably).
   Lab-attribute: annotates the attributes of lab procedures
   Medication-attribute: annotates the attributes of medications
   
2. Disease_symptom: automatically annotates symptoms of diseases, including:
   Bleeding_extraction: annotates bleeding symptoms
   Colorectal_cancer: annotates symptoms of colorectal cancer
3. Behavior:automatically annotates behaviors of patients , including:
   Smoking_status: annotates whether or not the patient is in a smoking status, and whether the patient has a smoking history. The figure below illustrates an example of using the disease-attribute pipeline in our pipeline library to annotate attributes and their relations with diseases.