The BioMedical Information Collection and Understanding System (BioMedICUS) is a system for large-scale text analysis and processing of biomedical and clinical reports. The system is being developed by the Natural Language Processing and Information Extraction program at the University of Minnesota Institute for Health Informatics. This is a collaborative project that aims to serve biomedical and clinical researchers, allowing for customization with different texts. Some small fixes for bugs that snuck into the 1.8.0 release New features and bug fixes. Switched models from being stored with MapDB to RocksDB. Added a disk based model for acronyms. Changed defaults from using in-memory models to using in-disk models. BioMedICUS will now run on less than 2gb of heap size. Added a numbers detector and a units of measurement detector. More-comprehensive models are available from http://athena.ahc.umn.edu/biomedicus-downloads/ for verified UMLS licensees.

We would like to acknowledge the following: Hongfang Liu - Mayo Clinic, Rochester, MN; Hua Xu - The University of Texas Health Science Center at Houston, Houston, TX; the members of the NLP/IE group at the University of Minnesota Institute for Health Informatics. Funding for this work was provided by: 1 R01 LM011364-01 NIH-NLM, 1 R01 GM102282-01A1 NIH-NIGMS, and U54 RR026066-01A2 NIH-NCRR.