Hi Shyam, I think that the key to your first question > how can execute the single function to run all this jobs in short time... Is in your code here:
1 final JCas jcas = JCasFactory.createJCas(); 2 jcas.setDocumentText( nextLine[0] ); 3 SimplePipeline.runPipeline(jcas, getUMLPipeline()); What you probably want to do is replace lines #1 and #2 with a CollectionReader, and then in #3 use a different SimplePipeline call that runs the pipeline using the CollectionReader instead of a static cas. There are commonly used CollectionReaders in ctakes-core. The most widely applicable is probably the FileTreeReader*, which reads a tree of ascii files. If you have some other source of text data then look around the code for something that might fit and let the devlist know if you can't find anything that fits your needs. I don't understand your second question: > how can i find sentence vised Dictionary words from string, give me a > solution for this.. Can you rephrase it and post to the devlist again? * one advantage that the FileTreeReader has is that it stores metadata on the input file tree placement, which can then be reproduced by output file writers like the html writer. Sean -----Original Message----- From: Ks Sunder [mailto:shyam...@gmail.com] Sent: Thursday, December 22, 2016 2:33 AM To: dev@ctakes.apache.org Subject: Re: Allergy Annotator Hi All, I have done the below code for finding medical terms from String information. step 1 : public static AnalysisEngineDescription getUMLPipeline() throws ResourceInitializationException, URISyntaxException{ AggregateBuilder builder = new AggregateBuilder(); builder.add(SimpleSegmentAnnotator.createAnnotatorDescription()); builder.add(SentenceDetector.createAnnotatorDescription()); builder.add(TokenizerAnnotatorPTB.createAnnotatorDescription()); builder.add(POSTagger.createAnnotatorDescription()); builder.add(ClinicalPipelineFactory.getNpChunkerPipeline()); builder.add(LvgAnnotator.createAnnotatorDescription()); try { builder.add( AnalysisEngineFactory.createEngineDescription( DefaultJCasTermAnnotator.class, AbstractJCasTermAnnotator.PARAM_WINDOW_ANNOT_PRP, "org.apache.ctakes.typesystem.type.textspan.Sentence", JCasTermAnnotator.DICTIONARY_DESCRIPTOR_KEY, ExternalResourceFactory.createExternalResourceDescription( FileResourceImpl.class, FileLocator.locateFile( "org/apache/ctakes/dictionary/lookup/fast/cTakesHsql.xml" ) ) ) ); } catch ( FileNotFoundException e ) { e.printStackTrace(); throw new ResourceInitializationException( e ); } return builder.createAggregateDescription(); } step 2: final JCas jcas = JCasFactory.createJCas(); jcas.setDocumentText( nextLine[0] ); SimplePipeline.runPipeline(jcas, getUMLPipeline()); for ( IdentifiedAnnotation entity : JCasUtil.select( jcas, IdentifiedAnnotation.class ) ) { if(entity.getOntologyConceptArr() != null){ add.append(entity.getCoveredText()+ ","); } } its working Fine.. But i have two quires.. 1. step1 , i am using Annotator step by step ... that time its taking more time load the all fuctions how can execute the single function to run all this jobs in short time... 2. how can i find sentence vised Dictionary words from string, give me a solution for this.. ...please give me a solutions for this issues.... regards, shyam k. On Thu, Dec 8, 2016 at 1:59 AM, Mullane, Sean *HS < sp...@hscmail.mcc.virginia.edu> wrote: > I'm reviving this thread with reference to negation detection. I > previously posted about this to the User list but this is probably a > more appropriate venue. > > The way the sentences are split on ":" makes the negation annotator > miss negation in lists of this form: > > Hyperlipidemia: Yes > Hypercholesterolemia: No > Chronic Renal Insufficiency: N/A > > I tried reversing order and removing ":"s and found that the negation > for Hypercholesterolemia is detected when in this form: > > Yes Hyperlipidemia > No Hypercholesterolemia > N/A Chronic Renal Insufficiency > > Our notes have quite a few places with this sort of list where good > negation detection is important but I haven't very good results. The > sentence segmentator sees this as 12 separate sentences, but I would > think proper behavior would be to consider this as 6 sentences > (breaking sentences on line break but not on colons). I see previous > discussion on the list about the sentence segmentator breaking on > newlines but little regarding colons. I would think in most cases it > would be more useful not to break on ":". Or is there an overriding reason > for the current behavior? > If changing the sentence segmentator isn't an option is there a > different way to configure the negation detection annotator that would > avoid this issue? > > Thanks, > Sean > > > > Hi, > > I am interested in the design decision of the sentence detector. > > Why does it split a sentence of the form "WORD1: WORD2 WORD3." into > two sentences "WORD1:" and "WORD2 WORD3."? Do other components of > cTAKES require such a sentence splitting? > > It would seem to me that it should remain one sentence. For example, > the smoking status detector has its own SentenceAdjuster that merges > some of such sentences back into one, because of this design. > > Thanks, Tomasz > > ________________________________________ From: Finan, Sean [ > sean...@childrens.harvard.edu] Sent: Friday, July 10, 2015 3:20 PM To: > de...@ctakes.apache.org Subject: RE: Allergy Annotator > > Hi Tom, > > It is exactly because the sentence detector splits "KEY:" from "VALUE" > that I > didn't suggest using sentences. Instead, I would just iterate over the > whole cas collection of medication events and attempt to match allergy > phrases ("allergic to medication") with text the note spanning from > event.begin-15 to > event.end+15 or whatever window size you prefer. > > Sean > > -----Original Message----- From: Tom Devel [mailto:deve...@gmail.com] > Sent: Friday, July 10, 2015 4:12 PM To: de...@ctakes.apache.org Subject: > Re: Allergy Annotator > > Sean and Dima, these are great suggestions, thanks so far. > > Sean, when looping over medication events as you say, I can see how it > is possible to take the textspan.Sentence of this MedicationMention, > and then do a regex check for the phrase structure as Dima said. > > But instead of textspan.Sentence, you mention "see any is included in > a phrase". > What cTAKES/UIMA class is related to this? > > Because if I would use textspan.Sentence, it would work for "The > patient is allergic to penicillin.", but cTAKES splits "ALLERGIES: > PENICILLIN, WHEAT" > into two sentences, so that the MedicationMentions here would not be > in the same sentence as the word "ALLERGIES". > > Thanks again, Tom > > On Fri, Jul 10, 2015 at 2:12 PM, Finan, Sean < > sean...@childrens.harvard.edu> > wrote: > > Hi Dima, Tom, > > I was thinking the same as Dima's first solution. Iterate through the > medication events and see any is included in a phrase as mentioned in > Tom's original email. Each phrase structure would have to be specified > beforehand. However, assigning appropriate CUIs would require having a > lookup table for each medication allergy. I think that would be the > simplest solution. > > Sean > > -----Original Message----- From: Dligach, Dmitriy [mailto: > dmit...@childrens.harvard.edu] Sent: Friday, July 10, 2015 2:50 PM To: > cTAKES Developer list Subject: Re: Allergy Annotator > > Hi Tom, > > If the patters are pretty simple, you could just add a few rules on > top of the cTAKES dictionary lookup output. Something of the kind > "allergic to <medication>" or "allergies: <medication1>, > <medication2>, <substance1>, ...". > > If these patterns are hard to express as rules, you should consider a > machine learning based sequence labeling route (e.g. something similar > to the cTAKES chunker). > > Dima > > -- Dmitriy (Dima) Dligach, Ph.D. Boston Children's Hospital and > Harvard Medical School (617) 651-0397 > > On Jul 10, 2015, at 13:40, Tom Devel <deve...@gmail.com<mailto: > deve...@gmail.com>> wrote: > > Sean, > > It would be a wider net, such that if an allergy is mentioned in the > clinical note, this is captured in the corresponding > IdentifiedAnnotation (or alternatively, if the IdentifiedAnnotation > class should not be changed with a new attribute, in a separate > allergy annotation). > > This annotator would then have to of course run after the clinical > pipeline has run and discovered all IdentifiedAnnotations. > > I am familiar with writing UIMA/cTAKES annotators, but not sure how a > new ML method could be integrated here for detecting allergies. Do you > have any thoughts about how to approach this in general? > > Thanks, Tom > > On Fri, Jul 10, 2015 at 11:54 AM, Finan, Sean < > sean...@childrens.harvard.edu<mailto:Sean.Finan@childrens.harvard.e > du>> > wrote: > > Hi Tom, > > Are you interested in catching all allergies or just a few specific > allergies for a study? If you are only concerned with a few then there > is a > (possibly) simple solution. If you are interested in throwing a wider > net then I think that a new module would need to be created; does > anybody reading this have an ML or regex style module? > > Sean > > -----Original Message----- From: Tom Devel [mailto:deve...@gmail.com] > Sent: Friday, July 10, 2015 12:42 PM To: de...@ctakes.apache.org<mailto: > de...@ctakes.apache.org> Subject: Allergy Annotator > > Hi, > > I would like to use/extend cTAKES to detect allergies. > > In the cTAKES publication (2010) > > https://urldefense.proofpoint.com/v2/url?u=http-3A__www.ncbi.nlm.nih.g > ov_pmc_articles_PMC2995668_&d=BQIFaQ&c=qS4goWBT7poplM69zy_3xhKwEW14JZM > SdioCoppxeFU&r=fs67GvlGZstTpyIisCYNYmQCP6r0bcpKGd4f7d4gTao&m=ZApJmGKjz > vFfNco5rRFVwSIyxmg4MRsxakfuXHbMZME&s=mGWu0XBCJqG2MI5qPlwIpGbQL5IYe7t5E > WcvhPYW7Lo&e= there is the mention that: "Allergies to a given > medication are handled by setting the negation attribute of that > medication to 'is negated'." > > However, in a post here in 2014 (RE: Allergy Indication) it is said > that cTAKES does not have a module for allergy discovery. > > 1. What is the current status of allergy detection in cTAKES? > > 2. I did some testing, while cTAKES discovers concepts about allegies > ("wheat allergy" is found as C0949570), using "ALLERGIES: PENICILLIN, > WHEAT" or "The patient is allergic to penicillin." does not give > penicillin or wheat annotations allergy status. > > How would I go about detecting these allergy mentions? > > Thanks, Tom > >
