Yes, and regarding your last paragraph: This is where disambiguation comes
into play. Here is one method:
https://www.cs.cmu.edu/afs/cs/project/jair/pub/volume23/montoyo05a-html/node9.html

I'm not sure how either MetaMap or BioMedICUS do disambiguation, but since
are both open source, they would be potential resources..

Greg--

On Fri, May 17, 2019 at 2:17 AM Peter Abramowitsch <[email protected]>
wrote:

> Seems like some kind of simple heuristic should work:    Isn't it just a
> case of looking at the in/out text offsets of the source text for an
> identified annotation and then comparing that with the canonical text of
> the CUI or SnomedID.   If the source text is just a few of characters (say
> less than 5) and the Levenstein difference between it and the canonical
> text is > than the length of the source text,  you're pretty sure to have
> an acronym.
>
> For instance if cTakes finds   "MI" and assigns SNOMED  22298006 or CUI
> C0027051 with canonical text "Myocardial Infarction"*, *then with the
> in/out offsets into the text you should be able to run this heuristic
>
> The problem (and I see this in my work) is that many acronyms have multiple
> meanings.  Thus, you may accurately be able to tell that your identified
> concept came from an acronym, but it was the wrong concept!!
>
> Peter
>
> On Thu, May 16, 2019 at 4:31 AM Greg Silverman <[email protected]> wrote:
>
> > Got it!
> >
> > Yes, I understand the formidability, given the need for disambiguation,
> > etc. Was just curious if this existed.
> >
> > Thanks!
> >
> >
> > On Wed, May 15, 2019 at 9:11 PM Finan, Sean <
> > [email protected]> wrote:
> >
> > > Hi Greg,
> > >
> > > Ok, that gives me a great vector toward addressing your needs.
> > >
> > > I don't know of any ctakes components that indicate whether or not
> > > discovered concepts come from acronyms, abbreviations or -replete- text
> > > mentions.
> > >
> > > There should be something that does that.   Open source ---->  Any
> > > champions available?
> > >
> > > Right now no abbreviation or metonym information is provided in the
> > > standard components.    If it can be extruded from source then it
> should
> > be
> > > provided.
> > >
> > > If anybody has such a component, please let us know !   This is a
> > > formidable (imio) nlp problem, so call your kudos with a solution!
> > >
> > > Sean
> > >
> > > ________________________________________
> > > From: Greg Silverman <[email protected]>
> > > Sent: Wednesday, May 15, 2019 9:21 PM
> > > To: [email protected]
> > > Subject: Re: acronyms/abbreviations [EXTERNAL]
> > >
> > > I'm just wondering how acronyms are identified as acronyms in cTAKES
> (for
> > > example, in MetaMap, there is an attribute in the Document annotation
> > with
> > > ids of where they are in the Utterance annotation; and in BioMedICUS,
> > there
> > > is an acronym annotation type, etc.). From examining the XMI CAS, it is
> > not
> > > obvious.
> > >
> > > We're extracting the desired annotations from the XMI CAS using a
> custom
> > > Groovy client.
> > >
> > > Thanks!
> > >
> > > On Wed, May 15, 2019 at 7:43 PM Finan, Sean <
> > > [email protected]> wrote:
> > >
> > > > Hi Greg,
> > > >
> > > > What exactly do you need ?
> > > >
> > > > There are a lot of output components that can produce different
> formats
> > > > containing various types of information.
> > > >
> > > > Do you prefer to parse ml ?  Or is columnized text output ok?  Does
> > this
> > > > go to a post-processing engine or a human user?
> > > >
> > > > Thanks,
> > > >
> > > > Sean
> > > > ________________________________________
> > > > From: Greg Silverman <[email protected]>
> > > > Sent: Wednesday, May 15, 2019 7:09 PM
> > > > To: [email protected]
> > > > Subject: acronyms/abbreviations [EXTERNAL]
> > > >
> > > > How can I get these from the XMI annotations?
> > > >
> > > > Thanks!
> > > >
> > > > Greg--
> > > >
> > > > --
> > > > Greg M. Silverman
> > > > Senior Systems Developer
> > > > NLP/IE <
> > > >
> > >
> >
> https://urldefense.proofpoint.com/v2/url?u=https-3A__healthinformatics.umn.edu_research_nlpie-2Dgroup&d=DwIFaQ&c=qS4goWBT7poplM69zy_3xhKwEW14JZMSdioCoppxeFU&r=fs67GvlGZstTpyIisCYNYmQCP6r0bcpKGd4f7d4gTao&m=Fj9pHse59o_GfrCnR_sqZ7ibEmMju2GDRj6hmEg5s9U&s=taqRUWLVp4l5699x1GSXNfIK6WkZXiAgKnA3CPmlfWk&e=
> > > > >
> > > > University of Minnesota
> > > > [email protected]
> > > >
> > > >  ›  evaluate-it.org  ‹
> > > >
> > >
> > >
> > > --
> > > Greg M. Silverman
> > > Senior Systems Developer
> > > NLP/IE <
> > >
> >
> https://urldefense.proofpoint.com/v2/url?u=https-3A__healthinformatics.umn.edu_research_nlpie-2Dgroup&d=DwIFaQ&c=qS4goWBT7poplM69zy_3xhKwEW14JZMSdioCoppxeFU&r=fs67GvlGZstTpyIisCYNYmQCP6r0bcpKGd4f7d4gTao&m=DSQkibRULBYY2ijgCfGWGPmrKD7gdrLjBbvnTbXozsA&s=pTRmMExWf-ju3IjLOdTelulzu0JW399BumarcAx5tRw&e=
> > > >
> > > University of Minnesota
> > > [email protected]
> > >
> > >  ›  evaluate-it.org  ‹
> > >
> >
> >
> > --
> > Greg M. Silverman
> > Senior Systems Developer
> > NLP/IE <https://healthinformatics.umn.edu/research/nlpie-group>
> > University of Minnesota
> > [email protected]
> >
> >  ›  evaluate-it.org  ‹
> >
>


-- 
Greg M. Silverman
Senior Systems Developer
NLP/IE <https://healthinformatics.umn.edu/research/nlpie-group>
University of Minnesota
[email protected]

 ›  evaluate-it.org  ‹

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