Hi Tim, Thanks for the prompt response. For starters, what I'd like to do process several hundred clinical narratives and extract the key items per narrative (CUI, RxForm, symptoms, relationships, smoking status, etc) for structured classification in a database. Since I'm looking at a collection of narratives for processing I see that the CPE tool would be ideal. You stated that "for more systematic access and processing we usually will write java code around an annotator that will use the ctakes API and typesystem to extract what we need." I'm currently using the user tool I'm guessing that I will need to graduate to the developer version in order to do what you stated. I appreciate your feedback. Regards, Paula -------------- Hi Paula, The typical way we visually inspect this information is in the CVD tool. Then for more systematic access and processing we usually will write java code around an annotator that will use the ctakes API and typesystem to extract what we need. Looking directly at the xml is usually about as useful as you seem to have found it (i.e., not very :) ).
What task are you trying to accomplish? If you just want to see what concepts are found for one file at a time that can be done in the CVD. If you are having trouble finding what you need there let us know. If you want an output file with all terms that were listed in any given input file that would probably require a little bit of programming. Tim From: [email protected] To: [email protected] Subject: Analyzing and processing cTakes NLP output Date: Tue, 8 Oct 2013 21:00:17 -0400 Hi Team (or is it just the Team of Samir ;-) I had processed a 2 1/2 page narrative from the CVD tool and exported to XCAS file in xml. I would like to extract the key items from the narrative that cTakes is known for such as identifying diseases/disorders, medications, signs/symptoms, and so forth. I quickly perused the file via xml browser and did see the SNOMED and RXNORM codes associated. I decided to printout out the file to markup the sections and to get an idea of how these codes relate back to the concepts identified by cTakes. My printer ran out of paper after about 60 pages and when I looked at the top sheet it was 1 out of 2243 pages! A 2 1/2 page narrative resulted in an xml file of over two thousand pages!!! I examined the first medication mapping. The numeric lines are my comments and everything else copy/pasted from XCAS file. 1. Identification of RxNorm code is 69749 but it's not associated with a concept so I copied '163573' and pasted in search in the xml file. See number 2 below for what retrieved. <uima.cas.FSArray _id="163573" size="1"> <i>163576</i> </uima.cas.FSArray> <org.apache.ctakes.typesystem.type.refsem.OntologyConcept _id="163539" codingScheme="RXNORM" code="69749" oid="69749#RXNORM"/> 2. Retrieved this result with some additional information such as the generic is false, but not med name mention. I copied "163581" and pasted in search. See number 3 below for what retrieved. _indexed="1" _id="163581" _ref_sofa="6" begin="9776" end="9784" id="530" _ref_ontologyConceptArr="163573" typeID="1" segmentID="SIMPLE_SEGMENT" discoveryTechnique="1" confidence="1.0" polarity="1" uncertainty="0" conditional="false" generic="false" subject="patient" historyOf="0"/> 3. Retrieved this result. The RxNorm code associated identifies Coumadin as a treatment. <org.apache.ctakes.assertion.medfacts.types.Concept _indexed="1" _id="227307" _ref_sofa="6" begin="9776" end="9784" conceptType="TREATMENT" conceptText="Coumadin" externalId="0" originalEntityExternalId="163581"/> Here are my questions: 1. is there any resources available that explains what the xml output file contains and the layout? Such as what does confidence of 1.0 and polarity of 1 and uncertainty of 0 refer to? 2. Are there any tools already existing that interpret the NLP output from cTakes and automatically structure and associate it to the concepts? Such as, automatically associate the RxNorm to the medication mention as illustrated above. As you see it took a few steps to associate the RxNorm code to the actual medication mention from the narrative. Thanks. Regards, Paula
