Welcome to the cTAKES community. Q1 – some people use the longest span. Q2 &Q3 – can you just use the text from the dictionary “Malignant neoplasm of liver (disorder)“. Alternatively you could modify cTAKES to save the text of the words that it matches when it is performing dictionary lookup. I would guess there is a term in the UMLS dictionary with the same code as Malignant neoplasm of liver (disorder) that just has the words “cancer of liver”, but there isn’t anything in cTAKES to give that to you just through a configuration change.
For “cancer of colon, liver and lung“, can you look at the chunk tag for liver. If it’s in a separate noun phrase (NP) from “cancer of colon” that would account for why cancer is not getting tied to liver in that case (but wouldn’t account for why the chunker is creating as a separate noun phrase) -- James From: [email protected] [mailto:[email protected]] On Behalf Of Dennis Lee Hon Kit Sent: Wednesday, August 21, 2013 1:10 PM To: [email protected] Subject: Concept annotation questions Hi Everyone, We are new to cTakes so please bear with our questions. We are using cTakes to annotate things like encounter diagnoses and referral notes and are especially interested with the SNOMED CT encodings. But we are not sure how to make sense of all the outputs. Example #1 In the example below, “cancer of colon, lung and liver” has been encoded with SNOMED CT and additional concepts that do not apply have been removed (e.g., general “cancer” concept, lung, colon and liver structures, etc). They have been plotted out by the begin/end positions. If the terms to do not align, its probably because the email only accepts plain text and a mono-spaced font is not the default. cancer of colon, lung and liver cancer of colon, lung and liver 93870000|Malignant neoplasm of liver (disorder)| cancer of colon, lung 363358000|Malignant tumor of lung (disorder)| cancer of colon 363406005|Malignant tumor of colon (disorder)| Question (1) – We had to do quite a bit of post-processing to remove inactive concepts, subtype concepts, concepts that are part of the defining attributes, etc. Are there a set of guidelines to help sort out the CUI or SNOMED CT codes that have been identified? Question (2) – How can we determine that “93870000|Malignant neoplasm of liver (disorder)|” refers to “cancer of liver” as opposed to using the begin/end string, which points to “cancer of colon, lung and liver”? Certainly we can try to do additional parsing but there are a lot of different scenarios to take into account. Question (3) – This relates to question 2, are we able to identify the original terms that were used for the concept matching or the exact description that was returned in the UMLS? While the CUI is helpful, the CUI can refer to tens or even hundreds of descriptions. ________________________________ Example #2 Switching the position of colon, lung and liver can result in different encodings. Once again, after removing additional concepts not needed (i.e., “cancer” and “colon structure”), we get the following. What happened to liver and lung cancer? cancer of colon, liver and lung cancer of colon 363406005|Malignant tumor of colon (disorder)| lung 39607008|Lung structure (body structure)| We have more questions but will start with these. Thank you in advance. Regards, Dennis
