My Sexy Voice is Now on the Internets

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We have officially released ARC: Automated Retrieval Console! My first big release for the VA and for the clinical informatics community. Not only do you get source code, binaries, documentation but also video recordings with voice narration.
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The Massachusetts Veterans Epidemiology Research and Information
Center (MAVERIC) is pleased to announce the release of the Automated
Retrieval Console (ARC). ARC is an open source Java-based toolkit
designed to automate and streamline the processes of clinical
information retrieval (i.e., natural language processing, information
extraction, concept mapping, machine learning, etc.).


We designed ARC with a few goals in mind. Our first goal is to allow
users to achieve acceptable levels of performance with no custom
software or rules development between tasks. Instead, ARC
automatically and iteratively evaluates combinations of NLP output
with supervised machine learning classification algorithms. Our
second goal is to free up developers and IR researchers to focus on
improving the science and technology by empowering end users to take
over many of the processes of IR. Finally, we hope to meet these
goals by building upon and contributing to a growing collection of
open source IR software.


To allow us to remain focused on streamlining the processes of
clinical IR, this first release of ARC takes on document-level
information retrieval. Interested users can download ARC with a with
a simple UIMA pipeline from our Google Code site or, thanks to the
generous cooperation of the National Library of Medicine, users can
download ARC with a full version of Dr. Guergana Savova’s cTAKES,
complete with UMLS-based knowledge base. For machine learning, this
version of ARC ships with Dr. Andrew McCallum’s Machine Learning for
Language Toolkit (MALLET).


More information, code, a step-by-step tutorial, and how-to videos for
using ARC can be found on our website at
http://research.maveric.org/MIGresearch.html.


ARC development was made possible by the generous support of the
Veterans Health Administration Office of Research and Development’s
Cooperative Studies Program and the Health Services Research and
Development program’s Consortium for Healthcare Informatics Research
(CHIR).