Funded undergraduate research opportunities: 2 positions, 5-10 hrs/week, starting Fall 2023

Funded graduate research assistant position: 1 position, 20hrs/week, starting Spring 2024

 

Dr. Ozlem Uzuner and team are interested in hiring 2 undrgraduates and one graduate student for a Natural Language Processing project on extracting medical event information.

 

Electronic health records (EHRs), detailing patient status and all aspects of clinical care, can greatly facilitate quality improvement and surveillance initiatives as well as revolutionize clinical research. The unstructured clinical narratives in EHRs document critical information, including medical problems, treatments, and diagnostic tests as well as the rationale for care and outcomes. This information can complement structured coded data used for diagnosis, care, triage, outcomes prediction, and clinical research. Recent decades have seen an increase in the development of clinical Natural Language Processing (NLP) and Information Extraction (IE) systems that target the identification of this critical information from clinical narratives.  This work explores use of deep learning and generative large language models for IE from clinical narratives.