https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3111590/
On Fri, May 17, 2019 at 8:23 PM Greg Silverman <[email protected]> wrote: > 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 ‹ > -- Greg M. Silverman Senior Systems Developer NLP/IE <https://healthinformatics.umn.edu/research/nlpie-group> University of Minnesota [email protected] › evaluate-it.org ‹
