University of Minnesota NLP/IE
The Natural Language Processing/Information Extraction program is a team of investigators at the University of Minnesota, Institute for Health Informatics. We use NLP/IE to process, extract, and encode information from unstructured biomedical and clinical texts, including clinical texts from the electronic health record. These techniques are then leveraged to support the invention of new healthcare and research applications and the investigation of healthcare interventions.
We release many of our projects as free and open source software on our GitHub organization page.Learn more » Downloads »
The BioMedical Information Collection and Understanding System leverages open source solutions for text analysis and provides new analytic tools for processing and analyzing text of biomedical and clinical reports.
MTAP is a framework for developing text analysis pipelines. It utilizes the gRPC Framework for communication between independently deployed, scalable, cross-language components.
Natural Lanaguage Processing - Patient Information Extraction from Research is an Information Extraction (IE) platform that provides direct access to patient data stored in free text of clinical notes.
The Natural Language Processing Artifact Discovery And Preparation Toolkit (NLP-ADAPT) is a collection of programs and scripts presented as a Virtual Machine (VM) image and as a repository of Docker and Kubernetes specifications (NLP-ADAPT-Kube). These formats are designed to help researchers who wish to use clinical Natural Language Processing get off the ground fast.