Introducing CLARK 2.0
CLARK 2.0 is a user friendly machine-learning classifier designed to answer a variety of translational research questions. This version of CLARK offers a new interface with additional features including the ability to analyze data based on both structured and unstructured data.
How can CLARK support my research?
CLARK is designed to supplement human effort and judgment in order to reduce time spent doing chart review, produce more robust computable phenotypes, and move studies to recruitment and/or data analysis faster. It can help to identify patient cohorts for a study when inclusion/exclusion criteria are framed as a classification problem.
In this session, we will:
- Discuss use cases ideal for CLARK
- Discuss the FHIR data formats required by CLARK
- Walk through the process for requesting data from TraCS and CDWH
- Provide an overview of how to write regular expressions, which are a core component of using CLARK
- Demonstrate using the new CLARK interface