Hi Deepal, I am assuming the mapping would be through UMLS CUI's. For example, for each CUI identified by the cTAKES UMLS Dictionary Lookup annotator.
Just putting some ideas out there: One would need a data structure to represent the Cardio Classes (perhaps a hashmap of some sort) that maps CUI's to the classes/instances. And then also a process to load that structure from the RDF (from either flat file, db, etc.) format? One might also need a place holder in the CAS (type system) to store the identified classes? --Pei > -----Original Message----- > From: Deepal Dhariwal [mailto:[email protected]] > Sent: Wednesday, January 16, 2013 11:21 AM > To: [email protected] > Subject: Re: Information Extraction using ontology > > Hello all, > > So what I am aiming is as follows: > 1. Extract UMLS medical terms from a given clinical narrative using ctakes > umls lookup annotator 2. Identify cardio vascular terms from above set. > These terms are classes / instances of heart failure ontology. I want to make > this mapping generic so that if in future I am targeting carcinogenic terms, > I'll > would just need to change underlying ontology. > 3. Lastly I want to run a reasoner over the rdf triples obtained from above > step. > > For example: Find the timi score of patient 1. Extract all medical terms from > clinical narrative 2. Extract cardio vascular terms such as whether the > patient > has congestive heart failure, whether he is an active smoker etc. using heart > failure ontology 3. Run the sparql query of form : > timi score = does patient have chf + age > 65 + active smoker? > > Hence I need guidance on an annotator that would map ctakes terms to > heart failure ontology and allow to run reasoner over it. Any suggestions > would be of great help. > > > Thanks > Deepal Dhariwal > > On Mon, Dec 31, 2012 at 9:00 AM, Lin, Chen > <[email protected]>wrote: > > > This mapping sounds very interesting and has potential usage for other > > projects. I will be curious to follow its progress. Thank you, Deepal, > > for digging this! > > > > Best, > > Chen > > > > Sent from my iPhone > > > > On Dec 30, 2012, at 6:43 AM, "Deepal Dhariwal" > > <[email protected]> > > wrote: > > > > > Hello Pei, > > > > > > I am aiming for an annotator that provides mapping between UMLS > > > CUI's and ontology classes. If I could write a generic code that > > > provides mapping between cTakes results and any ontology then it > > > might be useful to the community. > > > Let me know your views on this annotator. > > > > > > Thanks > > > Deepal Dhariwal > > > > > > On Fri, Dec 28, 2012 at 10:37 AM, Chen, Pei > > > <[email protected]>wrote: > > > > > >> Hi Deepal, > > >> If I understand correctly, you were planning to have an annotator > > >> that iterates through all of the UMLS CUI's identified by cTAKES > > >> and then map them to the heartfaid ontology class/code. > > >> I am not aware of anything that does specifically this, but there > > >> is an open ticket that is trying to do something similar for Drugs > > >> classes (RxNorm to NDF-RT mapping) ( > > >> https://issues.apache.org/jira/browse/CTAKES-107). > > >> It does seem like something that may be useful for others if you > > >> would like to contribute that to the community though... > > >> > > >> --Pei > > >> > > >>> -----Original Message----- > > >>> From: Deepal Dhariwal [mailto:[email protected]] > > >>> Sent: Thursday, December 27, 2012 10:28 PM > > >>> To: [email protected] > > >>> Cc: [email protected] > > >>> Subject: Re: Information Extraction using ontology > > >>> > > >>> Hello Pei, > > >>> > > >>> The dictionary is an ontology i.e. a .owl file (Reference: > > >>> http://lis.irb.hr/heartfaid/ontology/) . I am not sure whether it > > >>> is > > >> subset of > > >>> UMLS but its definitely based on UMLS since they have relations > > >>> such as 'UMLS Synonym' > > >>> An example of mapping terms would be: > > >>> 1. UMLS lookup annotator returns 'Hypertension' as medical > > >>> concept.I > > want > > >>> to assert that it corresponds to Hypertension class on this > > >>> ontology > > >> whose > > >>> parent is Blood Pressure and relations include TreatedBy, Could > > >>> Include > > >> etc. > > >>> > > >>> Hence I want to build a annotator that provides mapping between > > >>> ctakes annotator results and owl classes. Does the dictionary > > >>> lookup component allow to plug in dictionaries in .owl or .rdf format? > > >>> > > >>> Thanks > > >>> Deepal Dhariwal > > >>> > > >>> On Thu, Dec 27, 2012 at 10:31 AM, Chen, Pei > > >>> <[email protected]>wrote: > > >>> > > >>>> Hi Deepal, > > >>>> Within the dictionary lookup component, you can also plugin other > > >>>> custom dictionaries in additional to the UMLS ones. > > >>>> The dictionary itself can be in different formats (MySQL, HSQLDB, > > >>>> Lucene, CSV text file) and could be configured via the xml files. > > >>>> Is this what you were referring to? Do you have an example of > > >>>> "mapping terms to the corresponding classes?" > > >>>> Just curious, Is the heart ontology a subset of UMLS? > > >>>> > > >>>> Thanks, > > >>>> --Pei > > >>>> > > >>>>> -----Original Message----- > > >>>>> From: Deepal Dhariwal [mailto:[email protected]] > > >>>>> Sent: Thursday, December 27, 2012 12:17 AM > > >>>>> To: [email protected]; > > >>>>> [email protected] > > >>>>> Subject: Information Extraction using ontology > > >>>>> > > >>>>> Hello all, > > >>>>> > > >>>>> I have a heart ontology and I want to extract terms from a > > >>>>> clinical text > > >>>> that > > >>>>> correspond to classes in the ontology. cTAKES UMLS Lookup > > >>>>> Annotator returns UMLS terms from a given piece of text. Could I > > >>>>> modify the > > >>>> annotator > > >>>>> to extract terms from the ontology and is there is some other > > >>>>> component > > >>>> of > > >>>>> cTAKES that would allow me to do so. I am trying to set up a > > >>>>> cTakes > > >>>> pipeline > > >>>>> where I first extract medical terms from text using UMLS lookup > > >>>>> then > > >>>> filter > > >>>>> cardio vascular terms and identify relations between them using > > >>>>> an > > >>>> ontology. > > >>>>> > > >>>>> Thanks > > >>>>> Deepal Dhariwal > > >>>> > > >> > >
