Projects are posted to help find interested individuals with appropriate expertise to implement needs

Extracting Disease Phenotype Information for Patients with Rheumatic Disease from RISE Registry Clinical Notes


Project Description

The RISE registry includes complete EHR data for over 300 rheumatology practices across the United States, including over 400 million clinical notes. In this project, we will use natural language processing to extract key information from these clinical notes regarding the patient's phenotype and patient-reported outcomes. Initial concepts include rheumatoid arthritis patient-reported outcomes that are routinely recorded by rheumatologists in clinical notes, and organ manifestations of systemic lupus Erythematosus.


Probably yes


Required Skills

Natural Language Processing tools (NLTK, CTAKES, PyTorch-NLP, etc)

Required Course Work or Level of Knowledge
  • Machine Learning, intermediate - advanced
  • Acceptable Level of Education (eg. Undergrad, Grad Students, Post Docs, MD, PhD)
  • Graduate students,Postgraduates,Full-time workers who volunteer time
Additional Considerations

We are collaborating with the Stanford NLP team (Suzanne Tamang et al) but would like to also partner with someone at UCSF if available.


PI/Research group

Yazdany/Rheumatology Quality and Informatics Lab


Jinoos Yazdanym, [email protected]