=Paper=
{{Paper
|id=Vol-1747/BT301_ICBO2016
|storemode=property
|title=None
|pdfUrl=https://ceur-ws.org/Vol-1747/BT301_ICBO2016.pdf
|volume=Vol-1747
}}
==None==
<pdf width="1500px">https://ceur-ws.org/Vol-1747/BT301_ICBO2016.pdf</pdf>
<pre>
                                         NLP for the Institute
           Developing and Deploying an NLP Capability to Accelerate Cancer Research


                                                           Aaron Cohen
                                                Oregon Health & Science University
                                                  Portland, Oregon, United States
                                                        cohenaa@ohsu.edu


    Abstract— It has been well documented that a great deal of      characterization are two areas in particular where text sources
data useful for medical research is present in clinical narrative   could greatly supplement our current data.
text.
                                                                        The OHSU Knight Cancer Institute has begun a program to
    There is perhaps less discussion about how often what was       create a natural language processing (NLP) capability to extract,
structured data at its origin has become inaccessible except in     store, and link data from free text sources at the patient level,
free text form. This problem is further compounded in tertiary      and make this data available to researchers in a continuous,
care institutions, like the OHSU Knight Cancer Institute, where     reusable, efficient and timely manner through services delivery
the entire history of a referred patient's condition may only be    from the Translational Research Hub (TRH). This talk will
present in the electronic health record (EHR) as free text.         present the challenges, progress, and future goals of our program
                                                                    to build NLP capabilities that can help us use free text from the
    At the same time, future medical advances, such as in cancer    EHR to first support the transformation of cancer research with
research, will require much more complete patient data than has     the hopes of positively impacting clinical care in the future.
been previously available. Such advances include the discovery of
new cures, expanding early detection, and realizing the promise        Keywords— Text mining; Cancer research; Translational
of precision medicine. Phenotype description and outcome            medicine

</pre>