The Natural Language Processing / Information Extraction Program (NLP/IE)
The Natural Language Processing / Information Extraction (NLP/IE) Program (Director: Rui Zhang, PhD; Associate Director, Genevieve Melton-Meaux, MD, PhD) at the University of Minnesota Institute for Health Informatics is a team of investigators, postdoctoral researchers, developers, and students who work together on natural language processing (NLP) for a variety of clinical and biomedical tasks. We use NLP/IE to process, extract, and encode information from unstructured biomedical and clinical texts, including clinical notes from the electronic health record and biomedical literature. These techniques are then leveraged to support the invention of new healthcare and research applications and the investigation of healthcare interventions.
Current active areas of NLP/IE research for our group include redundancy detection in clinical texts; biomedical semantic similarity and relatedness measures; acronym, abbreviation, and symbol disambiguation; semantic role labeling; automated monitoring of adverse drug events; literature-based discovery for drug repurposing; algorithms to extract phenotyping; tools for interoperability and integration of NLP systems; and specialized modules for different types of clinical texts. In addition, our group has developed several NLP/IE resources including an open-source biomedical and clinical NLP/IE pipeline application, BioMedICUS (BioMedical Information Collection and Understanding System); an NLP ensemble tool with best in practice systems (NLP-ADAPT); and an NLP tool tailored self service for clinical and translational researchers (NLP-PIER). Several of our NLP/IE resourcesrelated to our projects are publicly available for other researchers.