Milena Gianfrancesco

Closed (1) Novel Approaches to Using Elecronic Health Record Data

Applications for fall 2021 are now closed for this project.

The Quality and Informatics Lab at UCSF (quil.ucsf.edu) is seeking highly motivated students to develop and study novel approaches to using electronic health record data. We are epidemiologists and rheumatologists with a special interest in rheumatoid arthritis and systemic lupus erythematosus and using EHR data to examine quality of care and medication safety in patients with autoimmune disease. Projects from our lab include 1) using machine and deep learning approaches to identify patients at risk of opportunistic infections; and 2) natural language processing and text mining to identify disease phenotypes from clinical notes. This exciting work will be guided by multidisciplinary collaborations with top scientists in rheumatology, clinical informatics, and bioinformatics at UCSF.

Depending on prior experience, the student will assist in developing machine/deep learning algorithms to predict disease outcomes, and refining natural language processing pipelines to phenotype rheumatic diseases. Other tasks may involve data management and literature reviews on various topics to be used for grants and publications.

Qualifications: Strong problem-solving skills and creative thinking are required. Applicants must possess excellent communication skills and be fluent in both spoken and written English. Prior experience with clinical databases, text-mining, advanced statistical modeling is a plus.

Weekly Hours: to be negotiated

Off-Campus Research Site: Virtual

Related website: http://quil.ucsf.edu